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Full text of "GEOLOGICAL DEPENDENCE OF RESISTANCE FACTORS FOR DEEP FOUNDATION DESIGN"

GEOLOGICAL DEPENDENCE OF RESISTANCE FACTORS 
FOR DEEP FOUNDATION DESIGN 
by 

CUONG VU 

B.S. Civil Engineering, Hanoi University of Civil Engineering, 2001 
M.S. Civil Engineering, University of Colorado at Boulder, 2004 



A thesis submitted to the 
Faculty of the Graduate School of the 
University of Colorado in partial fulfillment 
of requirement for degree of 
Doctor of Philosophy 
Civil Engineering 



2013 



©2013byCuongVu 
All rights reserved 



This thesis for the Doctor of Philosophy degree by 
Cuong Vu 
has been approved for the 
Civil Engineering Program 
by 



Nien-Yin Chang, Chair 

Stein Sture 
Brian Brady 
Jimmy Kim 
Trever Wang 

Aziz Khan 



Date: April 18,2013 



ii 



Cuong Vu (PhD, Civil Engineering) 

Geological Dependence of Resistance Factors for Deep Foundation Design 
Thesis directed by Professor Nien-Yin Chang 

ABSTRACT 

This research addresses the issue of geological dependence of deep foundation 
designs resistance factors for driven pile and drilled shaft designs in different 
locations. For the proof, two sets of databases were used: one from the NCHRP 507 
report and another driven pile and drilled shaft database with static load tests and soil 
profiles from the different locations in Vietnam were used to evaluate resistance 
factor design for different axial pile capacity prediction methods. Eight different static 
analysis methods were used for driven pile capacity evaluation: a- Tomlinson, a-API, 
X, P, Nordlund, Thurman, Meyerhof SPT, and the Shmertmann SPT method. For 
drilled shafts the FHWA and Reese & Wight methods were used. In the analyses the 
correlations between Nspt and soil parameters were used. First Order Second Moment 
(FOSM), First Order Reliability Methods (FORM) and Monte Carlo simulations were 
used to evaluate the based analyses in the determination of the resistance factors (O). 
The following notable benefits were attained in this project: 1) Resistance factors are 
made available for the LRFD designs of driven piles and drilled shafts in Vietnam; 2) 
The results show that the resistance factors vary with methods, geomaterial types and 
geological locations; 3) The found resistance factors (O) for Vietnam give 
substantially greater factored capacities as compared to the 2012 AASHTO-LRFD 
recommendations 

The form and content of this abstract are approved. I recommend its publication. 

Approved: Nien-Yin Chang 



iii 



ACKNOWLEDGEMENTS 

I am indebted, first and foremost, to my advisor Dr. Nien-Yin Chang for providing 
me the guidance and support and for his tireless advice during my study for this 
dissertation. I would also like to thank Dr. Stein Sture, Dr. Brian Brady, Dr. Jimmy 
Kim, Dr. Trever Wang and Dr. Aziz Khan for serving on the final examination 
committee. I would like to express my special thanks to my wife, Lan Anh Nguyen, 
for many years of her endurance, sacrifice, assistance, and encouragement, which 
made this accomplishment possible. I also thank my parents and my brother for their 
support and all of my friends who helped me in many ways to accomplish this 
research. 



iv 



CONTENTS 



Figures v 

Tables vii 

Chapter 

1. Introduction 1 

1 . 1 Problem statement 1 

1.2 Research objective 2 

1 .3 Research approach 2 

2. Literature Review 4 

2.1 History of LRFD Development 4 

2.2 Review of the Recommended Load Factors for Piles Designs 10 

2.3 ASD versus LRFD 16 

2.3.1 Allowable Stress Design (ASD) 17 

2.3.2 Load and Resistance Factor Design (LRFD) 19 

3. Axial Pile Capacity Prediction Methods 21 

3.1. Axial Loading Capacity of a Driven Pile 21 

3.1.1. Side resistance in cohesive soil 22 

3.1.1.1. a-Tomlinson method 22 

3.1.1.2. a-API revised method (1987) 24 

3.1.1.3. P-Burland method (1973) 25 

3.1.1.4. X-Method 27 

3.1.2. Tip resistance in cohesive soil 28 

3.1.3 Side resistance in cohesionless soil 29 

3.1.3.1 (3-Bushan method (1982) 29 

3.1.3.2 Nordlund method 29 

3.1.4. Tip resistance in cohesionless soil— Thurman method 33 

3.1.5. Empirical Methods 35 

3.1.5.1 Meyerhof method for piles in cohesionless soil 35 

3.1.5.2 Schmertmann method for SPT 36 

3.1.5.3 Nottingham and Schmertmann method for CPT 39 

3.2 Axial Loading Capacity of a Drilled Shaft 43 

3.2.1 Side resistance in cohesive soils 43 

3.2.1.1 FHWA method 43 

3.2.2 End bearing in cohesive soils 45 

3.2.2.1 FHWA method 45 



v 



3.2.3 Skin resistance in cohesionless soil 46 

3.2.3.1 FHWA method 46 

3.2.3.1 Reese and Wright method 47 

3.2.4 End bearing in cohesionless soil 47 

3.2.4.1 FHWA method 47 

3.2.4.2 Reese and Wright method 48 

3.2.5 Side resistance in rock 48 

3.2.6 Tip resistance in rock 49 

3.3 Piles Dynamic Analysis 51 

3.3.1 The Case Method 51 

3.3.2 The Energy Approach 52 

3.3.3 PDA Signal Matching Using CAPWAP 52 

3.4 Static Load Test 53 

3.4.1 ASTM Procedures 53 

3.4. 1 . 1 Standard Load Test Procedures 53 

3.4.1.2 Cyclic Load Test 54 

3.4. 1 .3 Quick Load Test Method for Individual Piles 54 

3.4.1.4 Constant Rate of Penetration 55 

3.4.2 Vietnamese Load Test Procedures 55 

3.5 Interpretation of Pile Load Test Results 55 

3.5.1 Davisson's Method 55 

3.5.2 The Limit Total Settlement Method 57 

3.5.3 DeBeer's Method 57 

3.5.4 Chin's Criterion 58 

3.6 Soil Properties from Insitu Tests 59 

3.6.1 Correlations between soil properties and SPT 60 

3.6.1.1 Undrained shear strength Su 60 

3.6.1.2 OCR for clay 61 

3.6.1.3 Effective stress friction angle of cohesionless soil 62 

3.6. 1 .4 Relative Density Dr of Cohensionless Soil 63 

3.6.2 Correlations between soil properties and CPT 64 

3.6.2.1 Undrained shear strength Su 64 

3.6.2.2 OCR for cohesive soil - Mayne 64 

3.6.2.3 The effective stress friction angle for cohensionless soil 65 

3.6.2.4 Relative Density Dr of Cohensionless Soil- Jamiolkowski 66 

3.6.3 Undrained Shear Strength of Clay vs Index Properties 67 

4. Evaluation of Resistance Factors By Calibration 68 

4.1 Fitting ASD to LRFD 69 

4.2 Reliability Analysis 69 

4.2.1 Resistance bias factor 70 



vi 



4.2.2 Probability density function 71 

4.2.3 The First Order Second Moment (FOSM) Method 72 

4.2.3.1 Reliability index p 72 

4.2.3.2 Recommended Target Reliability Index 79 

4.2.3.3. Efficiency of Different Methods 80 

4.2.3.4 Equivalent Factor of Safety 80 

4.2.3.5 Resistance Factor Calibration 81 

4.2.4 First-Order Reliability Method (FORM) Analysis 82 

4.2.5 Monte Carlo Simulation Method 86 

5. Resistance Factor Calibration for the Data from Difference Locations in NCHRP 
Report 507 90 

5.1 Introduction 90 

5.2 Calibration Resistant Factor for Driven Piles Using CAP WAP Method 90 

5.2.1 Resistance Factor for Different Locations by Using CAPWAP 
(BOR+EOD) Data 90 

5.2.2 Resistance Factor for Different Locations by Using CAPWAP 
(BOR)Data 94 

5.2.3 Resistance Factor for Different Locations by Using CAPWAP 

(EOD) Data 96 

5.3 Calibration Resistant Factor for Driven Piles Using Static Analysis 98 

5.3.1 Resistance Factor for Concrete Piles in Cohesionless for 

Different Locations 98 

5.3.2 Resistance Factor for Concrete Piles in Cohesive for 

Different Locations 99 

5.3.3 Resistance Factor for Concrete Piles in Mixed soil for 

Different Locations 100 

6. Data Collection from Vietnam 101 

6.1 Introduction 101 

6.2 General description of Vietnam geology 102 

6.2. 1 North Vietnam 1 02 

6.2.2 South Vietnam 106 

6.2.3 Central Vietnam 107 

6.3 Static Load Tests and Soil Profile from a site in Vietnam 108 

7. Calibration Resistance Factor for Driven Piles in Vietnam 113 

7.1 Procedure to Calibrate Resistance Factors for Driven Piles 113 

7.2 Collection of Driven Piles in Vietnam 114 

7.3 Measurement capacity of driven piles 1 14 

7.4 Nominal Capacity of driven piles 114 

vii 



7.4.1Nominal Capacity of Concrete Piles in Cohesionless Soils 115 

7.4.2 Nominal Capacity of Concrete Piles in Cohesive Soils 118 

7.4.3 Nominal Capacity of Concrete Piles in Mixed Soils 118 

7.5 Calibration of Resistance Factors 131 

7.5.1 Resistant factor for driven pile in Sand 132 

7.5.2 Resistant factor for driven pile in Clay 137 

7.5.3 Resistant factor for driven pile in Mixed Soil 143 

8. Calibration Resistance Factors for Drilled Shaft in Vietnam 161 

8.1 Procedure to Calibrate Resistance Factors for Drilled Shaft 161 

8.2 Collection of Drilled Shaft in Vietnam 161 

8.3 Measurement Capacity of drilled Shaft 162 

8.4 Nominal Capacity of Drilled Shaft 162 

8.4.1 Nominal Capacity of Concrete Piles in Mixed Soils 162 

8.5 Calibration of Resistance Factors for Drilled Shaft 167 

8.5.1 Resistant factor for drilled shaft in Mixed Soil 167 

8.5.2 Statistical sample size requirements for calibration the resistance factor for 
drilled shafts in Vietnam 178 

9. Conclusions and Recommendation 180 

9.1 Summary of Research 180 

9.2 Major Outcomes and Conclusions 181 

9.3 Recommendations 182 

9.4 Future Research 183 

Appendix 

A. Calibration Resistance Factor by Using FORM for Driven Pile using 

CAP WAP Method 184 

B. Calibration Resistance Factor by Using FORM for Driven Pile using Static 
Analysis 211 

C. Calibration Resistance Factor by Using FOSM for Driven Pile using 

CAPWAP Method 239 

D. Calibration Resistance Factor by Using FOSM for Driven Pile using Static 
Analysis 266 

E. Nominal and Measure Capacity of Driven Pile from Vietnam 275 

F. Histogram and Frequency Distribution of Bias Factor for Driven Piles from 

Vietnam 297 

G. Nominal and Measure Capacity of Drilled Shaft from Vietnam 390 

H. Histogram and Frequency Distribution of Bias Factor for Drilled Shaft 398 

References 422 



viii 



FIGURES 

Figure 

1.1 LRFD implementation for bridge foundations from survey in 2008 9 

2.1 Factor of Safety 13 

2.2 LRFD Design Approach 15 

3.1a Adhesion values for piles in cohesive soils (after Tomlinson, 1979) 23 

3.1b a factors; Tomlinson Method (Tomlinson, 1995) 24 

3.2 Comparison between a-Factors Calculated form API 1986 and 1987 25 

3.3 p factors (AASHTO 2007) 27 

3.4 Coefficient for driven pile piles after Vijayvergiya and Focht (1972) 28 

3.5 Design curve for evaluating K5 when (j) = 25 (Hannigan et al., after 
Nordlund, 1979) 30 

3.6 Design curve for evaluating K5 when (|) = 30 (Hannigan et al., after 
Nordlund, 1979) 31 

3.7 Design curve for evaluating K5 when (j) = 35 (Hannigan et al., after 
Nordlund, 1979) 31 

3.8 Design curve for evaluating K5 when ^ = 40 (Hannigan et al., after 
Nordlund, 1979) 32 

3.9 Relation 5/(|) and pile displacement (Hannigan et al., after Nordlund, 1979) 32 

3.10 Correction factor (CF) for K5 (Hannigan et al., after Nordlund, 1979) 33 

3.11 aT coefficient (FHWA--DRIVEN, 1998) 34 

3.12 Bearing capacity factor Nq'(FHWA-DRlVEN, 1998) 34 

3.13 Relationship between Maximum Unit Pile Toe Resistance qL (kPa) 

and Friction Angle for Cohesionless Soils (Meyerhof, 1976/1981) 35 

3.14 Ks and Kc ratio in cohesionless and cohesive soil, respectively (cited in 
McVay and Townsend, 1989) 39 

3.15 Tip resistance computation procedure—Nottingham 1975. (cited in McVay 

and Townsend, 1989) 40 

3. 16a Ks ratio in cohesionless 41 

3. 16b Kc ratio in cohesive soil 42 

3.17 Explanation of Portions of Drilled Shaft Not Considered in Computing 

Side Resistance in Clay (O'Neill! and Reese, 1999) 44 

3.18 Static pile load testing procedures according to ASTM 53 

3.19 Graphical representation of Davisson criterion 55 

3.20 Graphical representation of DeBeer method 56 

ix 



3.21a Load-settlement curve 57 

3.21b Replotted results for determination of CI and QL 57 

3.22 Su-SPT N Relationships by Kara 1974 (Kulhawy and Mayne, 1990) 60 

3.23 OCR--N Relationship (Kulhawy and Mayne, 1990) 61 

3.24 cp' by Peck, Hanson and Thombum (Kulhawy and Mayne, 1990) 61 

3.25 (p' by Schmertmann (Kulhawy and Mayne, 1990) 62 

3.26 Relative Density— N~Stress Relationship (Kulhawy and Mayne, 1990) 62 

3.27 op correlated with qc (OCR = op / a'O) (Kulhawy and Mayne, 1990) 63 

3.28 (p'tc correlated from qc for NC, uncemented quartz sands (Kulhawy and 
Mayne, 1990) 64 

3.29 Correlation between Dr and qc (uncorrected for boundary effect) (Kulhawy 
and Mayne, 1990) 65 

3.30 Correlation between Normalized Undrained Shear Strength and Liquidity 
Index for NC Clays (after Kulhawy and Mayne, 1990) 66 

4.1 Distribution of load and resistance and reliability index, P 75 

4.2 Reliability definition based on standard normal probability density function 78 

4.3 Comparison of Esteva and Withiam methods to obtain reliability index, p 79 

4.4 Redundant vs. non-redundant pile support, Paikowsky, et al. (2004) 80 

4.5 Limit state function and pdf of basic random variables (Baecher and 
Christian 2003) 83 

4.6 Transformed basic variable space. (Baecher and Christian 2003) 83 

5.1 Resistance Factor <}) for Driven Piles Using CAP WAP (EOD+BOR) with p 
=2.33 92 

5.2 Resistance Factor <^ for Driven Piles Using CAP WAP (EOD+BOR) 

with p =3.0 93 

5.3 Resistance Factor ^ for Driven Piles Using CAPWAP (BOR) 

with (3=2.33 95 

5.4 Resistance Factor cj) for Driven Piles Using CAPWAP (BOR) 

with p =3.0 95 

5.5 Resistance Factor (}) for Driven Piles Using CAPWAP (EOD) 

with p =2.33 97 

5.6 Resistance Factor ^ for Driven Piles Using CAPWAP (EOD) 

with p =3.0 97 

6. 1 Vietnamese Map 101 

6.2 The deep of bearing layer (gravel) in Hanoi 105 

6.2 Red River Shipyard Project Site Plan 108 



X 



6.4a Static Load Test Data and Chin's Method for A5-2 (350x350) Concrete 

Pile Ill 

6.4b Static Load Test Data and Chin's Method for Al-5 (350x350) Concrete 

Pile Ill 

6.4c Static Load Test Data and Chin's Method for B 1-2 (350x350) Concrete 

Pile Ill 

6.4d Static Load Test Data and Chin's Method for B5-2 (350x350) Concrete 

Pile 112 

6.4e Static Load Test Data and Chin's Method for B 10-2 (350x350) Concrete 

Pile 112 

7.1a Measure Capacity Davisson's versus 80% Chin Method 115 

7.1b Measure Capacity Davisson's versus 1" settlement 116 

7.2a: Prediction Capacity using Nordlund method vs. Measure Capacity of 

Concrete Piles in Cohesionless Soils (North and South of Vietnam) 116 

7.2b: Prediction Capacity using Nordlund method vs. Measure Capacity of 

Concrete Piles in Cohesionless Soils (North and South of Vietnam) 117 

7.2c: Prediction Capacity using Schmertmann SPT method vs. Measure 

Capacity of Concrete Piles in Cohesionless Soils (North, Central and South 

of Vietnam) 117 

7. 2d: Prediction Capacity using Meyerhof SPT method vs. Measure Capacity of 
Concrete Piles in Cohesionless Soils (North, Central and South of Vietnam) ...118 

7.3a: Prediction Capacity using a-TomUnson method vs. Measure Capacity of 
Concrete Piles in Cohesive Soils- Su Irom Terzaghi-Peck in North, Central 
and South of Vietnam 119 

7.3b: Prediction Capacity using a-Tomlinson method vs. Measure Capacity of 
Concrete Piles in Cohesive Soils-Su from Hara in North, Central and South 
of Vietnam 120 

7.3c: Prediction Capacity using a-API method vs. Measure Capacity of 
Concrete Piles in Cohesive Soils-Su from Terzaghi-Peck in North, Central 
and South of Vietnam 120 

7.3d: Prediction Capacity using a-API method vs. Measure Capacity of 

Concrete Piles in Cohesive Soils-Su from Hara in North, Central and South 

of Vietnam 121 

7.3e: Prediction Capacity using X method vs. Measure Capacity of Concrete 
Piles in Cohesive Soils-Su from Terzaghi and Peck in North, Central and 
South of Vietnam 121 

7.3f: Prediction Capacity using X method vs. Measure Capacity of Concrete 
Piles in Cohesive Soils-Su from Hara (North, Central and South of Vietnam) 
122 



xi 



7.3g: Prediction Capacity using P method vs. Measure Capacity of Concrete 

Piles in Cohesive Soils (North, Central and South of Vietnam) 122 

7.3h: Prediction Capacity using Schmertmann SPT method vs. Measure 
Capacity of Concrete Piles in Cohesive Soils (North, Central and South of 
Vietnam) 123 

7.4al: Prediction Capacity using a-Tomlinson, Nordlund, Thurman method vs. 
Measure Capacity of Concrete Piles in Mixed Soils- Su from T-P, cp from P- 
H-T (North, Central and South of Vietnam) 123 

7.4a2: Prediction Capacity using a-Tomlinson, Nordlund, Thurman method vs. 
Measure Capacity of Concrete Piles in Mixed Soils - Su from Hara, cp from 
P-H-T(North, Central and South of Vietnam) 124 

7.4a3: Prediction Capacity using a-Tomlinson, Nordlund, Thurman method vs. 
Measure Capacity of Concrete Piles in Mixed Soils (North, Central and 
South of Vietnam) 124 

7.4a4: Prediction Capacity using a-Tomlinson, Nordlund, Thurman method vs. 
Measure Capacity of Concrete Piles in Mixed Soils (North, Central and 
South of Vietnam) 125 

7.4b 1 Prediction Capacity using a- API, Nordlund, Thurman method vs. 
Measure Capacity of Concrete Piles in Mixed Soils (North, Central and 
South of Vietnam) 125 

7.4b2: Prediction Capacity using a-API, Nordlund, Thurman method vs. 
Measure Capacity of Concrete Piles in Mixed Soils (North, Central and 
South of Vietnam 126 

7.4b3: Prediction Capacity using a-API, Nordlund, Thurman method vs. 
Measure Capacity of Concrete Piles in Mixed Soils (North, Central and 
South of Vietnam) 126 

7.4b4: Prediction Capacity using a-API, Nordlund, Thurman method vs. 
Measure Capacity of Concrete Piles in Mixed Soils (North, Central and 
South of Vietnam) 127 

7.3c 1: Prediction Capacity using X, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils (North, Central and South of 
Vietnam) 127 

7.4c2: Prediction Capacity using X, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils (North, Central and South of 
Vietnam) 128 

7.4c3: Prediction Capacity using X, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils (North, Central and South of 
Vietnam) 128 

7.4c4: Prediction Capacity using X, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils (North, Central and South of 
Vietnam) 129 

xii 



7.4dl: Prediction Capacity using P method vs. Measure Capacity of Concrete 

Piles in Mixed Soils (North, Central and South of Vietnam) 129 

7.4d2: Prediction Capacity using P method vs. Measure Capacity of Concrete 

Piles in Mixed Soils (North, Central and South of Vietnam) 130 

7.4el : Prediction Capacity using SPT method vs. Measure Capacity of 

Concrete Piles in Mixed Soils (North, Central and South of Vietnam 130 

7.5a Histogram and frequency distribution of bias factor >^1 for 58 cases of 
concrete piles in Sand using the Nordlund method ((j): Peck, Hanson and 
Thombum) in Vietnam 134 

7.5b Resistant factor calibration for 58 cases of concrete piles in Sand using the 

Nordlund method ((|): Peck, Hanson and Thornbum) in Vietnam 134 

7.6a Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using Nordlund , ShmertmannSPT and Mayhoft SPT method for 
Cohesionless Soil in Vietnam with p =2.33 136 

7.6b Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using Nordlund ,Shmertmann SPT and Mayhoft SPT method for 
Cohesionless Soil in North of Vietnam with P =2.33 136 

7.7a Histogram and frequency distribution of bias factor Xl for 50 cases of 

concrete piles in Clay using the a-Tomlinson method (Su: Peck) in Vietnam ... 138 

7.7b Resistant factor calibration for 50 cases of concrete piles in Clay using the 

a-Tomlinson method (Su: Peck) in Vietnam 138 

7.8a Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a- API method, X method, P-Burland, 
Shmertmann SPT method for Cohesive Soil in Vietnam with P =2.33 142 

7.8b Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a-API method, X method, P-Burland, 
Shmertmann SPT method for Cohesive Soil in North of Vietnam with p 
=2.33 142 

7.8c Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a-API method, X method, P-Burland, 
Shmertmann SPT method for Cohesive Soil in Central of Vietnam with p 
=2.33 143 

7.9a Histogram and frequency distribution of bias factor X2 for 165cases of 
concrete piles in Mixed soils using the a-Tomlinson and Nordlund/Thurman 
method (Su: Hara, (j): P) in Vietnam 149 

7.9b Resistance factor calibration for 165 cases of concrete piles in Mixed soils 
using the a-Tomlinson and Nordlund/Thurman method (Su: Hara, ^: Peck, 
Hanson and Thornbum) in Vietnam 149 

7.10a Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a-API method. A, method, P-Burland, 
Nordlund-Thurman, Shmertmann SPT method in Vietnam with P =2.33 154 



xiii 



7.10b Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a- API method, X method, P-Burland, 
Nordlund-Thurman, Shmertmann SPT method in North of Vietnam with P 
=2.33 154 

7.1 Ic Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a- API method, X method, P-Burland, 
Nordlund-Thurman, Shmertmann SPT method in Central of Vietnam with P 
=2.33 155 

7.1 Id Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a- API method, X method, P-Burland, 
Nordlund-Thurman, Shmertmann SPT method in South of Vietnam with P 
=2.33 155 

7.12 Number of data versus the resistance factor O with PT =3.0 for driven piles 
in mixed soil from North, Central and South of Vietnam using a-Tomlinson 
& Nordlund-Thurman method ( Su from Terzaghi and Peck and O from 

Peck, Hanson and Thornbum) 156 

7.13 Number of data versus the resistance factor Owith pT =3.0 for driven piles 
in mixed soil from North, Central and South of Vietnam using P Burland & 
Northlund-Thurman method ( cD from Peck, Hanson and Thomburn) 157 

7.14 Number of data versus the resistance factor O with pT =3.0 for driven 
piles in mixed soil from North, Central and South of Vietnam using 
Shmertmann SPT method 157 

7.15 Number of data versus the resistance factor O with pT =3.0 for driven piles 
in mixed soil from North, Central and South of Vietnam using a-Tomhnson 

& Nordlund-Thurman ( Su from Terzaghi and Peck) 158 

7.16 Number of data versus the resistance factor O with pT =3.0 for driven 
piles in mixed soil from North, Central and South of Vietnam using A, & 
Nordlund-Thurman ( Su from Terzaghi and Peck) 158 

8.1a Prediction Capacity using FHWA method (Su: T-P) vs. Measure Capacity 

of Drilled Shaft using 1" Criterion in Mixed Soils in Vietnam 163 

8.1b Prediction Capacity using FHWA method (Su: Hara) vs. Measure Capacity 

of Drilled Shaft using 1" Criterion in Mixed Soils in Vietnam 163 

8.1c Prediction Capacity using R&W method (Su: T-P) vs. Measure Capacity of 
Drilled Shaft using 1" Criterion in Mixed Soils in Vietnam 164 

8. Id Prediction Capacity using R&W method (Su: Hara) vs. Measure Capacity 

of Drilled Shaft using 1" Criterion in Mixed Soils in Vietnam 164 

8.2a Prediction Capacity using FHWA method (Su: Terzaghi & Peck) vs. 
Measure Capacity of Drilled Shaft using 1" Criterion in Mixed Soils in 
Vietnam 165 



xiv 



8.2b Prediction Capacity using FHWA method (Su: Hara) vs. Measure Capacity 

of Drilled Shaft using 0.5%D Criterion in Mixed Soils in Vietnam 165 

8.2c Prediction Capacity using R&W method (Su: T-P) vs. Measure Capacity of 
Drilled Shaft using 0.5%D Criterion in Mixed Soils in Vietnam 166 

8.2d Prediction Capacity using R&W method (Su: Hara) vs. Measure Capacity 

of Drilled Shaft using 0.5%D Criterion in Mixed Soils in Vietnam 166 

8.3a Histogram and frequency distribution of bias factor Xl for 92 cases of 
drilled shaft in Mixed soils using the FHWA method (Su: Terzaghi, Peck) 
and using 1" criterion in Vietnam 171 

8.3b Resistance factor calibration for 92 cases of drilled shaft in Mixed soils 
using the FHWA method (Su: Terzaghi, Peck) and using 1" criterion in 
Vietnam 171 

8.4a Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 1" criterion 
settlement in North, Center and South of Vietnam 173 

8.4b Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 1" criterion 
settlement in North of Vietnam 174 

8.4c Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 1" criterion 
settlement in South of Vietnam 174 

8.5a Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 0.5% D 
criterion settlement in North, Center and South of Vietnam 176 

8.5b Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 0.5% D 
criterion settlement in North of Vietnam 177 

8.5c Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 0.5% D 
criterion settlement in South of Vietnam 177 

8.6 Number of data versus the resistance factor O with px =3.0 for drilled shaft 
(using the FHWA method and Su from Hara) 178 

8.7 Number of data versus the resistance factor O with PT =3.0 for drilled shaft 
using the Reese and Wright method (Su from Terzaghi and Peck) 179 

8.8 Number of data versus the resistance factor O with pT =3.0 for drilled shaft 
using the Reese and Wright method (Su from Hara) 179 



XV 



TABLES 



Table 

2.1 Resistance Factor for Driven Piles for Estimating the Axial Geotechnical 
Pile Capacity Using Reliability-Based Calibration (modified after Barker, et 

al, 19991) 10 

2.2 Resistance Factors for Drilled Shafts for Estimating the Ultimate Axial 
Shaft Capacity Using Reliability-Based Calibration (Modified Barker, et al., 
1991b) 10 

2.3 ReUability Index of Case Method Prediction (After McVay et al, 1998) 11 

2.4 Resistance factor for Case Method prediction (After McVay et al., 1998) 11 

2.5 Comparison of Resistance Factors for Geotechnical Strength Limit State in 
Axial Loaded Piles and Drilled Shafts (After McVay et al., 1998) 12 

2.6 Summary of calibration results for driven piles, static analyses 12 

2.7 Relationship between Numbers of Load Tests Conducted per Site and cj) 

(after Paikowsky, et al, 2004) 13 

2.8 Number of DjTiamic Tests with Signal Matching Analysis to be Conducted 
During Production Pile Driving (after Paikowsky, et al., 2004) 13 

2.9 Summary of Resistance Calibration Results for Driven Piles, Static 

Analyses 14 

2.10 Summary of Calibration Results for Drilled Shaft, Static Analyses 15 

2.1 1: Summary of the reported LRFD resistance factors, sorted according to 

different pile types, static analysis methods, and soil types (after 2008 Iowa 

State survey) 16 

2.12. Factor of Safety on Ultimate Axial Geotechnical Capacity Based on Level 

of Construction Control (AASHTO, 1997) 18 

2.13 Factors of Safety on Ultimate Geotechnical Capacity Based on Design Life 

and Level of Construction Control (Reese and O'Neill, 1988) 18 

3.1 Side resistance-Schmertmann method for SPT 37 

3.2 Tip resistance-Schmertmann method for SPT 37 

3.3 Critical depth ratio—Schmertmann method for SPT 38 

3.4 Represent CPT Cf values (after the FHWA, 2007) 41 

3.5 Methods for calculating axial loading capacity of a driven pile 42 

3.6 Values of Ir and Nc* (Reese, et al, 2006) 46 

3.7 (3 for Gravelly sands and Gravels (Rollins et al., 2005) 47 

3.8 Estimation of (O'Neil and Reesse, 1999) 48 

3.9 Methods for calculating axial loading capacity of a drilled shaft 49 

3.10a: Correlations between SPT N- values and Dr, ^, and y soil (after Bowles, 

1977) 59 

3.10b: Correlations between SPT N-values and qu and y (after Bowles, 1977) 59 



xvi 



3.1 1 Summary correlations between SPT N-values and soil parameters 63 

3.12 Summary Correlations between CPT and soil parameters 65 

4. 1 Resistance Factors Calibrated by Fitting with WSD for yD = 1 .25 and yL = 

1.75 (After McVay et al., 1998) 69 

4.2 \qd, Xql, COVqd, COVql as recommended by AASHTO (cited in Withiam 
etal, 1997) 71 

4.3 Relationship between Probability of Failure and Reliability Index for 
Lognormal Distribution (After Withiam et al., 1997) 78 

5.1a Resistance Factors for Driven Piles using CAP WAP (BOR+EOD) for 

Different Locations 89 

5.1b Resistance Factors for Driven Piles using CAP WAP (BOR+EOD) for 

Different Locations 89 

5.2 Resistance Factors for Driven Piles using CAP WAP (BOR) for Different 
Locations 94 

5.3 Resistance Factors for Driven Piles (EOD) using CAPWAP for Different 
Locations 96 

5.4a Resistance Factors for Concrete Piles in Cohesionless Soil 98 

5.4b Resistance Factors for Concrete Piles in Cohesionless Soil for Florida Data 

Only 98 

5.5a Resistance Factors for Concrete Piles in Cohesive Soil 99 

5.5b Resistance Factors for Concrete Piles in Cohesive Soil for Louisiana Data 

Only 99 

5.6a Resistance Factors for Concrete Piles in Mixed Soil 100 

5.6b Resistance Factors for Concrete Piles in Mixed Soil for Florida Data Only 100 

5.6c Resistance Factors for Concrete Piles in Mixed Soil for Louisiana Data 

Only 101 

6. 1 General soil profile in North Vietnam 103 

6.2 Mean Values Properties of Each Soil Type North Vietnam 104 

6.3a Properties of Organic Clay Layer in South Vietnam 106 

6.3 b Friction Angle and Cohesion of Organic Clay Layer in South Vietnam 107 

6.4a Properties of Non-Organic Clay Layer in South Vietnam 107 

6.4 b Friction Angle and Cohesion of Inorganic Clay Layer in South Vietnam 107 

6.5 Summary SPT value of each Layer 109 

6.6 Summary of Soil Properties of Clay Layer 109 

6.7 Summary of Soil Properties of Sand Layer 110 



xvii 



7.1 Bias factor X for driven pile in Cohesionless Soil using Nordlund 
,Shmertmann SPT and Mayhoft SPT method with Davission's criterion in 
North, Center and South of Vietnam 132 

7. la Summary of calibration resistance factor for driven pile using Nordlund 
,ShmertmannSPT and Mayhoft SPT method in North, Center and South of 
Vietnam 135 

7.1b Summary of calibration resistance factor for driven pile using Nordlund 

,Shmertmann SPT and Mayhoft SPT method in North of Vietnam 135 

7. Ic Summary of calibration resistance factor for driven pile using Nordlund 

,Shmertmann SPT and Mayhoft SPT method in Center of Vietnam 140 

7.2 Bias factor X for driven pile in cohesive soil using a-Tomlinson,a-APl 
method, X method, P-Burland, Shmertmann SPT method with Davission's 
criterion in North, Center and South of Vietnam 139 

7.2a Summary of calibration resistance factor for driven pile using a- 

Tomlinson, a- API method, X method, P-Burland, Shmertmann SPT method 

in North, Center and South of Vietnam 140 

7.2b Summary of calibration resistance factor for driven pile using a- 

Tomlinson, a- API method, X method, P-Burland, ShmertmannSPT method 

in North of Vietnam 141 

7.2c Summary of calibration resistance factor for driven pile usinga-Tomlinson, 
a-API method, X method, P-Burland, ShmertmannSPT method in Central of 
Vietnam 141 

7.3 Summary of calibration resistance factor for driven pile using a-Tomlinson, 
a-APl method, X method, P-Burland, Nordlund-Thurman, ShmertmannSPT 
method in North, Center and South of Vietnam 144 

7.3a Summary of calibration resistance factor for driven pile usinga-Tomlinson, 
a-APl method, X method, P-Burland, Nordlund-Thurman, ShmertmannSPT 
method in North, Center and South of Vietnam 150 

7.3b Summary of calibration resistance factor for driven pile usinga-Tomlinson, 
a-API method, X method, P-Burland, Nordlund-Thurman, ShmertmannSPT 
method in North of Vietnam 151 

7.3c Summary of calibration resistance factor for driven pile usinga- 
Tomlinson, a-API method, X method, P-Burland, Nordlund-Thurman, 
Shmertmann SPT method in Central of Vietnam 152 

7.3d Summary of calibration resistance factor for driven pile using a- 
Tomlinson, a-API method, X method, P-Burland, Nordlund-Thurman, 
Shmertmann SPT method in South of Vietnam 153 

7.4 Recommendation of Resistance Factor for Driven Pile in Vietnam with Pt = 

3.0 160 



xviii 



8.1 Bias Factor for drilled Shaft in Mixed Soil using FHWA and Reese & 

Wright method with 1" and 0.5% D settlement criterion 

8.1a Summary of calibration resistance factor for drilled shaft using FHWA and 
Reese & Wright method with 1" criterion settlement in North, Center and 
South of Vietnam 

8.1b Summary of calibration resistance factor for drilled shaft using FHWA and 
Reese & Wright method with 1" criterion settlement in North of Vietnam 

8. Ic Summary of calibration resistance factor for drilled shaft using FHWA and 
Reese & Wright method with 1" criterion settlement in South of Vietnam 

8. Id Summary of calibration resistance factor for drilled shaft using FHWA and 
Reese & Wright method with 0.5%D settlement in North, Center and South 
of Vietnam 

8. le Summary of calibration resistance factor for drilled shaft using FHWA and 
Reese & Wright method with 0.5%D settlement in North of Vietnam 

8. If Summary of calibration resistance factor for drilled shaft using FHWA and 
Reese & Wright method with 0.5%D settlement in South of Vietnam 1 



xix 



1. Introduction 

1.1 Problem Statement 

Since AASHTO introduced the LRFD method to account for uncertainties associated 
with estimated loads and resistances, bridge superstructures have been designed using 
the LRFD method in most of the U.S. but the ASD method is still used for bridge 
foundation design in practice. This can lead to inconsistent levels of reliability 
between superstructures and substructures. In an effort to maintain a consist level of 
reliability, the Federal Highway Administration and AASHTO set a mandate date of 
October 1, 2007 after which all federal-funded new bridges including substructures 
shall be designed using the LRFD method. The deadline has passed but the 
implementation of LRFD methodology for bridge foundation design is still 
experiencing much difficulty since the resistance factors for deep foundation in the 
AASHTO LRFD specifications are based on commonly use design methods and 
nationwide general geologic conditions that do not address local specific conditions. 
For example, the driven pile and drilled shaft database used in the existing AASHTO 
code is based on the data gathered by the Federal Highway Administration (FHWA) 
and the Florida DOT and may not reflect the soil conditions of other states with less 
data. Therefore, the resistance factors recommended in the existing AASHTO code 
need to be verified before being applied to local soil condition and design practice. 
Each state or region has its unique geological formation and the methods of analysis 
given by the AASHTO LRFD specifications do not consider this variance formation. 
Direct application of the AASHTO LRFD specifications without considering 
geologic conditions in design methodology could lead to overly conservative or un- 
conservative design. Thus, the resistance factors must be developed for the unique 
soil types of the region, in which the piles are used, incorporating the many years of 
pile design and construction experience in that region. 



1 



1.2 Research Objective 

The objectives of this study are two-fold 

• To assess the geographical locations dependence of resistance factor from 
difference locations by separating the database in NCHRP 507 report 
(Paikowsky, et al., 2004) and using it to calibrate the resistance factors of deep 
foundations for each of the different locations. 

• To assess the geographical locations dependence of resistance factors in 
Vietnam by calibrating the resistant factors of drilled shafts and driven piles 
for North, South and Central Vietnam 

1.3 Research Approach 

To achieve the research objectives, the following tasks are to be undertaken: 

Task 1 : Review the different design approaches used for bridge pile foundations 

including ASD and LRFD methods 
Task 2: Review the design methods for the bearing capacity of driven piles and 

drilled shafts 

Task 3: Review the methods for calibrating the resistance factors including fitting 
LRFD to ASD, First Order Second Moment Method (FOSM), First Order 
Rehabihty Method (FORM) and the Monte Carlo Simulation Method 

Task 4: Separate the data from the NCHRP Report 507 by different locations and 
calibrate the resistance factors for deep foundations using dynamic and static 
analysis methods for each state and other locations in the world. 

Task 5: Collect the top-down static load test for driven piles and drilled shafts and 
soil profiles from North, South and Central Vietnam and perform static analyses 
of pile bearing capacity for each test using the different analysis methods. 

Task 6: Calibrate the resistance factors by using First Order Second Method (FOSM), 
First Order Reliability Method (FORM) and Monte Carlo Simulation Method 



2 



for the different static analysis methods, for the different pile types (drilled 
shafts and driven piles), and for the different geologic regions: North, South and 
Central Vietnam. 

Task 7: Recommend the resistance factors for deep foundation design including 
driven piles and drilled shafts in Vietnam 

Task 8: Compare the resistance factors for deep foundations for different locations in 
the U.S. and Vietnam the draw the conclusions as to the dependency of 
resistance factors on geological and geographical locations. 



3 



2. Literature Review 

2.1 History of LRFD Development 

From the early 1800s until the mid-1950s, the ASD approach has been used in 
the design of superstructures and substructures, in which all uncertainty in loads and 
material resistance is combined in a factor of safety or allowable stress. And after the 
mid-1950s, the LRFD approach has been developed for structural design with the 
objective of ensuring a uniform degree of reliability throughout the structure. The 
basic hypothesis of the LRFD is quantifying the uncertainties based on probabilistic 
approaches, which aims to achieve engineered designs with consistent levels of 
reliability. In the LRFD approach, different load types and combinations are 
multiplied by load factors while resistances are multiplied by resistance factors, and 
the factored loads should not exceed the factored resistances. 

Until late 1970's the province of Ontario in Canada decided not to use 
AASHTO Standard Specification for Highway Bridges and started to develop its own 
bridge design code. It also decided to base its specification on probabihstic limit 
states. In 1979 the first edition of the Ontario Highway Bridge Design Code (OHBDC) 
was released to the design community as North America's first calibrated, reliability 
based limit state specification. In 1983, the second edition of the LRFD Code with 
Commentary was adopted in Ontario and its use became mandatory. This code was 
developed based on a reliability index of 3.5 for superstructure elements. The 
corresponding results of using similar reliability index in geotechnical engineering 
were not encouraging since the foundation elements generally became larger and the 
design became more conservative. The third edition of the Ontario Bridge Code with 
Commentary was adopted in 1992, and its use yields more reasonable design of 



4 



foundations but still more conservative than the previous AASHTO-based designs 
using ASD method. 

Load and Resistance Factor Design (LRFD) was adopted by the American 
Association of State Highway and Transportation Officials (AASHTO) as an 
alternative method for the design of bridge superstructures in the early 1970's. At that 
time, allowable stress design was the only method available in AASHTO for the 
design of the bridge foundations. In 1987 AASHTO initiated a research program, 
administered by the National Cooperative Highway Research Program to develop 
LRFD method for Bridge Foundations (NCHRP 24-4), and concluded with a report 
NCHRP 343 (Barker, et al, 1991) "Manuals for the Design of Bridge Foundations". 
This research provided the basis for development of Section 10-Foundations and 
Section 1 1 -Abutments, Piers and Walls in the 1994 AASHTO LRFD Specification. 
The research used a combination of calibration by fitting to ASD, and reliability 
theory. When reliability theory was used, they used First Order Second Moment 
(FOSM) method for preliminary analyses and First Order Reliability Method 
(FORM) for final analyses. The primary source of statistical data was from load test 
results provided by Reese and O'Neill (1988) and Horvath and Kenney (1979), for a 
total of 76 load test case histories. For piles in clay, the primary source of statistical 
data was Irom Sidi (1986). The number of pile load tests was not specifically 
reported, but was described as numerous. The specific source of statistical data for 
piles in sand, at least with regard to model error, was reported as from Robertson, et 
al. (1988) and Horvitz et al. (1981) load test data for the CPT method. For the 
Meyerhof SPT method in sand. Barker, et al. considered the bias and GOV of the SPT 
test to be adequate for the development of model error statistics for this method. The 
resistance factor for the driven piles and drilled shafts from NCHRP 343 report are 
summarized in table 2. 1 and 2.2 



5 



In 1997 the Florida Department of Transportation (FDOT) developed LRFD 
Code for their bridge design to deal with problems that they encountered in practice 
such as the unique characteristics of Florida geology- soft limestone formation, lime 
rock backfill materials which were widely used in south Florida- and the FDOT 
design methods of driven piles and drilled shafts developed through the FDOT 
research projects were not considered in the NCHRP 24-4 research project in 
developing the Resistant Factors . They performed calibrations of their current ASD 
practice to the LRFD format usiTO load combinations and load factors. The 
reliability index was calculated for the safety factor used in their ASD practice, and a 
target reliability index was chosen. The resistance factors were then calibrated for the 
target reliability index. This document makes an important contribution since it 
represents the thoughts of a progressive geotechnical organization in a transportation 
agency and it deals with their response to problems they saw with the LRFD Bridge 
Code. The result from NCHRP report are summarized in table 2.3, 2.4 and 2.5. 

Withiam et al. (1998) authored a manual titled 'LRFD for Highway Bridge 
Substructures' published by the Federal Highway Administration (FHWA). Using 
this manual, FHWA offered a National Highway Institute (NHI) training course too 
many of the state DOT's in an effort to implement LRFD for foundation design. 

Kyung Jun Kim et al. (2002) developed the resistance factors for the design of 
driven piles in North Carolina. The resistance factors were developed for the different 
static pile capacity analysis methods, for the different pile types, and for the unique 
geologic coastal and piedmont regions of the state. These factors were developed 
within the framework of reliability theory utilizing the Pile Driving Analyzer test and 
static load test data embodying the uncertainties associated with the capacity 
prediction model, the pile type and geometry, and the soil parameters. The form of 
probability distribution function describing the pile capacity is studied, and the 



6 



associated parameters are quantified. The first order reliability method (FORM) was 
used to evaluate the reliability index of the current design methods and to select the 
target reliability index, which was then used to develop the resistance factors. 

Paikowsky et al. (2004) presented calibration resistance factor on deep 
foundations, published as NCHRP Report 507 for the development of LRFD for 
bridge foundation design, which became the basis for the 2007 AASHTO bridge 
design specification. This report gathered an extensive database of load test results for 
driven piles and drilled shaft and grouped the data in the pile load test database by 
soil type, resistance prediction method, the type of construction technique used and 
pile type to develop the statistics needed for the reliability analyses they conducted. 
Paikowsky, et al. (2004) treated the loads and the resistance as the random variables. 
They evaluated the distribution of the data, comparing the probability density graphs 
for the actual data to the theoretical normal and lognormal distributions, to choose 
which distribution function to use to characterize the data. In most cases, they found 
that the resistance data was lognormally distributed. Paikowsky, et al. (2004) fully 
relied upon the results obtained from reliability theory to determine resistance factors, 
though calibration by fitting to ASD was also checked. For reliability theory, they 
relied upon the results from the advanced reliability methods (i.e., Hasofer and Lind, 
1974), which they termed "First Order Reliability Method (FORM)." While they 
compared the results from FORM to MVFOSM calibration results, they relied on the 
FORM resuhs. 

In 2004, the AASHTO-LRFD Oversight Committee conducted a survey among 
the State Departments of Transportation (DOTs) to monitor the degree of 
implementation of the LRFD approach for bridge substructure design (Moore, 2004), 
with a follow-up survey in 2005. The committee found that 12 states had fully 



7 



implemented the LRFD method for foundation design in 2004 and increased to 16 in 
2005. 

Nien-Yin Chang el al. (2006) sent a questionnaire to all state DOTs as part of 
the development of the LRFD strategic plan for foundation design practice in 
Colorado. Only 28 DOTs responded to the questionnaire, and revealed that less than 
22% of the respondents had either implemented or began implementation of LRFD 
for bridge foundations, while the remaining 78% had not even attempted the LRFD 
implementation. 

In 2007, the AASHTO-LRFD Oversight Committee updated the LRFD 
implementation survey in their progress report (Moore, 2007), which indicated that 
44 states would have fully implemented the LRFD approach for all new bridges by 
the FHWA mandated deadline of October 1, 2007. 

In 2008 the Iowa State University conducted the survey the current extent of 
LRFD implementation in the design of bridge foundations in the United States. 
Among the DOTs who responded as using the LRFD method for foundation design, 
46% are using regionally calibrated resistance factors based on SLT database and 
reliability theory, 23% are using regionally calibrated factors by fitting to ASD, while 
31% are using the geotechnical resistance factors as specified in the current AASHTO 
Specifications (2007) 

In 2008 LADOT conducted the research to find the resistance factor for driven 
piles in soft Louisiana soils. Forty two precast prestressed concrete piles with 
different lengths and sizes that were loaded to failure were investigated in this study. 
Statistical analyses were conducted to evaluate the different pile design methods, 
including the static design method (a-method and Nordlund method), three different 
direct CPT design methods: Schmertmann method, De Ruiter and Beringen method. 



8 



and Bustamante and Gianeselli (LCPC) method, and dynamic measurement with 
signal matching analysis (CAPWAP) method. In addition, reliability analyses based 
on first order second moment (FOSM) method were conducted to calibrate the 
resistance factors (cp) for the different design methods needed in the LRFD design of 
single piles. 



Figure 1.1 LRFD implementation for bridge foundations (after 2008 Iowa State survey) 

In 2012 IDOT conducted research to calibrate regionally LRFD resistance 
factors for bridge pile foundations in Iowa based on reliability theory, taking into 
consideration the current local practices. The resistance factors were developed for 
general and Iowa's static analysis methods used for the design of pile foundations as 
well as for dynamic analysis methods and dynamic formulas used for construction 
control. The report showed a substantial gain in the factored capacity compared to the 
2008 AASHTO-LRFD recommendations and gave comprehensive design tables and 
charts for implementation of the LRFD approach, ensuring uniform reliability and 
consistency in the design and construction processes of bridge pile foundations 




9 



2.2 Review of the Recommended Load Factors for Piles Designs 



Table 2. 1 Resistance Factor for Driven Piles for Estimating the Axial Geotechnical Pile 
Capacity Using Reliability-Based Calibration (modified after Barker, et al., 1991). 



Pile 
Length 
(m) 


Pt 


(j) Values by Method of Axial Pile Capacity Estimation 


a 






CPT 


SPT 


Type I 


Type II 


Type I 


Type II 


10 


2.0 


0.78 


0.92 


0.79 


0.53 


0.65 


0.59 


0.48 


30 


2.0 


0.84 


0.96 


0.79 


0.55 


0.71 


0.62 


0.51 


10 


2.5 


0.65 


0.69 


0.68 


0.41 


0.56 


0.48 


0.36 


30 


2.5 


0.71 


0.73 


0.68 


0.44 


0.62 


0.51 


0.38 


Average cj) 


0.78 


0.74 


0.56 


0.55 


0.43 


Selected cj) 


0.70 


0.50 


0.55 


0.55 


0.45 



Type I refers to soils with Su < 50 kPa, Type II refers to soils with Su > 50 kPa 



Table 2.2 Resistance Factors for Drilled Shafts for Estimating the 
Ultimate Axial Shaft Capacity Using Reliability-Based Calibration 
(Modified Barker, et al, 1991b) 



Shaft 
Length 
(m) 




cj) Value by Method of Axial Shaft Capacity Estimation 


Reese & O'Neill 
(1988) 
Shafts in Clay 


Horvath & Kenney 
(1979) 
Shafts in Rock 


Carter & Kulhawy 
(1987) 
Shafts in Rock 


3 


2.5 




0.70 


0.49 


10 


2.5 


0.72 


0.73 


0.56 


30 


2.5 


0.80 






3 


3.0 




0.56 


0.37 


10 


3.0 


0.72 


0.59 


0.43 


30 


3.0 


0.71 






Average cj) 


0.74 


0.65 


0.46 


Selected cj) 


0.65 


0.65 


0.55 



10 



Table 2.3 Reliability Index of Case Method Prediction (After McVay et al, 1998) 



on/OT 




COVr 


Xr 


COVqd 




COVql 






EOD 


BOR 


EOD 


BOR 


EOD 


BOR 


1 


3.04 


2.40 


0.325 


0.318 


1.355 


1.052 


0.1 


1.05 


0.18 


1.15 


2.5 


2 


J.VO 


2.44 


0.325 


0.318 


1.355 


1.052 


0.1 


1.05 


0.18 


1.15 


2.5 


3 


3.10 


2.46 


0.325 


0.318 


1.355 


1.052 


A 1 

0.1 


1.05 


A 1 O 

0.18 


1 1 ^ 

1.15 


2.5 


4 


3.11 


2.47 


0.325 


0.318 


1.355 


1.052 


0.1 


1.05 


0.18 


1.15 


2.5 


5 


3.12 


2.48 


0.325 


0.318 


1.355 


1.052 


0.1 


1.05 


0.18 


1.15 


2.5 


6 


3.13 


2.49 


0.325 


0.318 


1.355 


1.052 


0.1 


1.05 


0.18 


1.15 


2.5 


7 


3.13 


2.49 


0.325 


0.318 


1.355 


1.052 


0.1 


1.05 


0.18 


1.15 


2.5 


8 


3.13 


2.49 


0.325 


0.318 


1.355 


1.052 


0.1 


1.05 


0.18 


1.15 


2.5 


9 


3.14 


2.50 


0.325 


0.318 


1.355 


1.052 


0.1 


1.05 


0.18 


1.15 


2.5 



Table 2.4 Resistance Factor for Case Method Prediction (After McVay et al., 1998) 



Qd/Dl 


Resistance Factor cj) 


EOD 


BOR 




p=2.0 


p=2.5 


p=3.0 


p=2.0 


p=2.5 


p=3.0 


1 


0.85 


0.70 


0.58 


0.66 


0.55 


0.46 


2 


0.81 


0.67 


0.56 


0.64 


0.53 


0.44 


3 


0.79 


0.66 


0.54 


0.62 


0.52 


0.43 


4 


0.78 


0.65 


0.54 


0.61 


0.51 


0.42 


5 


0.77 


0.64 


0.53 


0.61 


0.51 


0.42 


6 


0.77 


0.64 


0.53 


0.60 


0.50 


0.42 


7 


0.77 


0.63 


0.53 


0.60 


0.50 


0.41 


8 


0.76 


0.63 


0.52 


0.60 


0.50 


0.41 


9 


0.76 


0.63 


0.52 


0.60 


0.50 


0.41 



11 



Table 2.5 Comparison of Resistance Factors for Geotechnical Strength Limit State in 
Axial Loaded Piles and Drilled Shafts (After McVay et al., 1998) 



Method/Soil/Condition 


Resistance Factor 


AASHTO 
(1994) 


FDOT RESEARCH 


Reliability 


Fitting 


Ultimate 
Bearing 
Resistance 
of Single 
Piles 


Skin Friction and End Bearing: 
Sand 

SPT-method 


0.45 


0.65 


0.70 


Skin Friction and End Bearing All 
Soils 

Load Test 

Pile Driving Analyzer 


0.80 
0.70 


0.75 
0.65 


0.70 
0.55 


Drilled 
Shaft 


All Soils 


0.45-0.65 


0.50-0.65 


0.55 



Table 2.6 Summary of Calibration Results for Bearing of Driven Piles, Dynamic Analyses 



Condition /Resistance Determination Method 


ASDFS 
Current 
Practice 


(|) from 
Calibration by 
fitting to ASD 
(Current 
Practice) 


Reliability 
Theory, 
NCHRP 
507 


AASHTO 
2007 


Driving criteria established by static load 
test(s), production pile quality control by 
calibrated wave equation, or minimum driving 
resistance combined with minimum delivered 
hammer energy from the load test(s). For the 
last case, the hammer used for the test pile(s) 
shall be used for the production piles. 


2.0 


0.69 


See Table 
2.9 


Values in 
Table 2.7 
(0.55 to 0.90) 


Driving criteria established by dynamic test 
with signal matching at BOR, of at least one 
production pile per pier, but no less than the 
number of tests per site provided in Table 2.8 
Production pile quality control of remaining 
piles by calibrated wave equation. 


2.25 


0.61 


0.65 


0.65 


Wave equation analysis at EOD without pile 
dynamic measurements or load test. 


2.75 


0.5 


0.39 


0.40 


FHWA-Modified Gates pile formula at EOD. 


3.5 


0.39 


0.38 


0.40 


Engineering News Record dynamic pile 
formula at EOD, with built in FS of 6 removed 
from formula. 


3.5 


0.39 


0.26 


0.10 



12 



Table 2.7 Relationship between Numbers of Load Tests Conducted per Site 
and (}) (after Paikowsky, et al., 2004) 



Number of Load 
Tests per Site 


Resistance Factor, 


Site Variability 




Low 


Medium 


High 


1 


0.80 


0.70 


0.55 


2 


0.90 


0.75 


0.65 


3 


0.90 


0.85 


0.75 


^4 


0.90 


0.90 


0.80 



Table 2.8 Number of Dynamic Tests with Signal Matching Analysis to be Conducted 
During Production Pile Driving (after Paikowsky, et al., 2004) 



Site Variability 


Low 


Medium 


High 


Number of Piles 


Number of Piles with Dynamic Tests and 


Located within Site 


Signal Matching Analysis Required (BOR) 


^15 


3 


4 


6 


16-25 


3 


5 


8 


26-50 


4 


6 


9 


51-100 


4 


7 


10 


101-500 


4 


7 


12 


>500 


4 


7 


12 



13 



Table 2.9 Summary of Resistance Calibration Results for Driven Piles, Static Analyses. 



Soil 
type 


Design 
Method 


Pile 
Type 


ASD FS 

Used 
NCHRP 
343 


Calibration 
by fitting 
To ASD 
NCHRP 
343 


Reliability 
Theory 
NCHRP 
343 


AASHTO 
96/2004 


Reliability 
Theory, 
NCHRP 
507 


4" 

AASHTO 
2007 




a-Tomlinson 
method 


concrete 










0.36 






pipe 


2.5 


0.61 


0.70-0.90 


0.7 


0.25 


0.35 




H-Pile 










0.40 




Clay 


X-method 


concrete 










0.48 




pipe 


2.5 


0.61 


0.49-0.62 


0.55 


0.24 


0.40 






H-Pile 










0.37 






(3-method 


concrete 










0.32 






pipe 


2.5 


0.61 


0.68 


0.5 


0.14 


0.25 






H-Pile 










0.19 






Nordlund/ 
Thurman 


concrete 










0.42 




Sand 


pipe 










0.56 


0.45 


H-Pile 










0.46 






Meyerhof 
SPT 


concrete 










0.19 






pipe 


4.0 


0.38 


0.46-0.49 


0.45 


0.31 


0.30 




H-Pile 










0.42 






Schmertn 
CPT 


All piles 


2.5 


0.61 


0.54-0.57 


0.55 


0.51 


0.50 


Rock 


Canadian 
Geo. Society 
1985 


All piles 


3.0 






0.4 




0.45 



14 



Table 2.10 Summary of Calibration Results for Drilled Shaft, Static Analyses 



Soil 
type 


Condition 

and 
Location 


Design Method 


ASD FS 

Used 
NCHRP 

343 


Calibration 
by fitting to 

ASD 
NCHRP 343 


<^ 

Reliability 

Theory 
NCHRP 343 


AASHTO 
96/98/04 


from 
Reliability 
Theory, 
Recommended 
in 

NCHRP 507 


<? 

AASHTO 
2007 


Clay 


Side 
Resistance 


a- method 
(Reese and O Neill 
1988) 


2.5 


0.612 


0.72 


0.65 


0.24 to 0.28 
recommended 
0.30 


0.45 


Base 
Resistance 


Total Stress 
(Reese and 
O'Neill 1988) 


2.75 


0.55 


0.55 


0.24 to 0.28 
recommended 
0.30 


0.40 


Sand 


Side 
Resistance 


method 
(Reese and O'Neill 
1988) 


2.5 


0.61 






0.25 to 0.73 
recommended 
0.40 


0.55 


Base 
Resistance 


(Reese and 
O'Neill 1988) 


2.75 


0.55 




0.25 to 0.73 
recommended 
0.40 


0.50 


Mixed 
Soil 


Side and 
Base 
Resistance 
sand/clay 


Reese and 
O'Neill 1988 


- 


- 


- 


- 


yj.jz. 10 yj.oy 
recommended 
0.50 to 0.70 


u.z)-> lor 
side, 0.50 
for base 




IGM's 


O'Neill and 
Reese 1999 


- 


- 


- 


- 


0.57 to 0.65 


0.60 for 
side, 0.55 
for base 


Rock 


Side 
Resistance 


Carter and 
Kulhawy (1988) 


2.5 


0.61 


0.43 


0.55 


0.45 to 0.49 


0.50 


Horvath and 
Kenney (1979) 


2.5 


0.61 


0.73 


0.65 




0.55 


Base 
Resistance 


Canadian 
Geotechnical 
Society (1985) 


3.0 


0.51 




0.50 




0.50 


Pressure Method 
(Canadian 
Geotechnical 
Society 1985) 


3.0 


0.51 




0.50 




0.50 


Bearing 


Block failure 


Clay 


2.3 


0.67 




0.65 




0.55 



15 



Table 2. 1 1 : Summary of the reported LRFD resistance factors, sorted according to different 



State 


Pile Type 


Static analysis methods 


Resistance Factors 


Cohesive 


Cohesionless 


Sand 


Clay 


Mixed 


AK 


ClDH(l) 


a-method 


SPT-method 


0.45 


N/A 


N/A 


CA* 


Steel H-piles 


CPT-method 


Nordlund 


0.45 


0.35 


N/A 


CO 


CIDH 


SPT-method 


SPT-method 


0.1 


0.9 


0.5 


CT* 


Prestressed 


Iowa blue book 


Iowa blue book 


0.65 


0.65 


0.65 


FL* 


CIDH 


CPT-method 


Nordlund 


0.65 


0.65 


0.65 


HI 


Steel H-piles 


p-method 


p-method 


0.65 


0.65 


0.65 


lA* 


Steel H-piles 


Iowa blue book 


Iowa blue book 


0.725 


0.725 


0.725 


ID* 


Steel H-piles 


P-method 


SPT-method 


0.45 


0.45 


0.45 


IL 


Open- pipe 


a-method 


Nordlund 


0.7 


0.7 


0.7 


MA* 


Open end pipe 


Iowa blue book 


Nordlund 


0.65 


0.65 


0.65 


NH* 


Closed-pipe 


a-method 


Nordlund 


0.45 


0.35 


N/A 


NJ* 


CIDH 


a-method 


Nordlund 


0.45 


0.35 


0.4 


NM* 


Steel H-piles 


p-method 


Nordlund 


0.35 


0.45 


N/A 


NV 


Steel H-piles 


a-method 


Nordlund 


0.35 


0.25 


N/A 


PA* 


Steel H-piles 


P-method 


Nordlund 


0.5 


0.5 


0.5 


PA 


Steel H-piles 


^.-method 


SPT-method 


0.45 


0.55 


0.55 


UT* 


Steel H-piles 


a-method 


Nordlund 


0.5 


0.7 


0.7 


WA 


Steel H-piles 


Iowa blue book 


Iowa blue book 


0.5 


0.5 


0.5 


WY 


Steel H-piles 


CPT-method 


Nordlund 


0.45 


0.35 


0.35 



*State DOTs having pile static load test database; (1) CIDH: Cast-In-Drillec 



Hole Shafts: 



2.3 ASD versus LRFD 

According to surveying from Paikowsky et al. (2004) the averaging the 
responses for driven piles and drilled shafts, about 90% of the respondents used ASD, 



16 



35% used AASHTO Load Factor Design (LFD), and 28% used AASHTO Load and 
Resistance Factors Design (LRFD). 



2.3.1 Allowable Stress Design (ASD) 

The design of deep foundations has traditionally been based on the allowable 
stress design (ASD), which involves applying a factor of safety (FS) to account for 
uncertainties in the applied loads and soil resistance. The magnitude of FS depends on 
the importance of the structure, the confidence level of the material properties, and 
design methodology. FromNCHRP 507 report, among the respondents using ASD to 
evaluate capacity, 95% used a global safety factor ranging from 2.0 to 3.0, depending 
on construction control and 5% used partial safety factors of 1.5 to 2.0 for side 
friction (3.0 for drilled shafts) and 3.0 for end bearing (2.0 to 3.0 for drilled shafts). 

For the strength limit state in ASD, the estimated loads (or stresses) Z Q i are 
restricted as shown bellow: 

^^IQ: (2.1) 

where: Rn = Nominal resistance 

Fs = Factor of safety 

ZQi = Load effect (dead, live and environmental loads). 
For the Service Limit State, un-factored loads are used to calculate deformations, 
and these deformations are compared to the maximum tolerable values. 
The advantage of ASD is its simplicity but the shortcomings of this approach are: 

• Does not account for variability of loads and resistances. 

• Does not embody a reasonable measure of strength 

• The FS is applied only to resistance and selection of a FS is subjective, and 
does not provide a measure of reliability in terms of probability of failure. 



17 



UmMATE RESISTANCE ^ 
APPLIED LOAD Q 

r— SAFETY MAIK5IN = R„ - Q 
RESISTANCE OR LOADS (R, Q) 

Figure 2.1 Factor of Safety 



Table 2.12. Factor of Safety on Ultimate Axial Geotechnical Capacity Based on Level of 
Construction Control (AASHTO, 1997). 



Basis for Design and Type of 
Construction Control 


Increasing Design/Construction Control 


Subsurface Exploration 


X 


X 


X 


X 


X 


Static Calculation 


X 


X 


X 


X 


X 


Dynamic Formula 


X 










Wave Equation 




X 


X 


X 


X 


CAPWAP Analysis 






X 




X 


Static Load Test 








X 


X 


Factor of Safety (FS) 


3.50 


2.75 


2.25 


2.0 


1.90 



Table 2. 13 Factors of Safety on Ultimate Geotechnical Capacity Based on Design 
Life and Level of Construction Control (Reese and O'Neill, 1988) 



Design Life (Type of Structure) 


Required Minimum Factor of Safety (FS)*" 


Poor Quality 
Control 


Normal Quality 
Control 


Good Quality 
Control 


200 to 500 years (large 
bridges & monumental structures) 


3.5 


2.3 


1.7 


75 to 100 years (typical rail & 
road bridges & large buildings) 


2.8 


1.9 


1.5 


25 to 50 years (industrial buildings) 


2.3 


1.7 


1.4 



(1) Assumes good-quality geotechnical information and reliable model. 




18 



2.3.2 Load and Resistance Factor Design (LRFD) 

The LRFD specifications as approved by AASHTO (AASHTO, 1994/2007) 
recommend the use of load factors to account for uncertainty in the loads, and 
resistance factors for the uncertainty in the material resistances. This safety criterion 
can be written as: 



where: 

Rn = Nominal resistance, 

r\ = Load modifier to account for effects of ductility, redundancy and 
operational importance. The value of r\ usually ranges from 0.95 to 1.00. In 
this research, r\ = 1.00 is used 
Qi = Load effect 

Yi = Load factor. Based on current AASHTO recommendation, the following 

factors are used 

Yd = 1 .25 for dead load 

Yl = L75 for live load 

O = Resistance factor—Usually ranges from 0.25 to 0.8. 
For driven piles and drilled shaft, we have 



(^Rn > TlZ Yl Qi 



(2.2) 



OR„> 11.25 Qd+L75 Ql 



(2.3) 



If different resistance factors are used for tip and side resistance, then 
OsRs + OpRp > Z 1.25 Qd+ L75 Ql 



(2.4) 



where: Rs = Side resistance 
Rp = Tip resistance 

(^s, Resistance factors for side and tip resistance, respectively. 



19 



LOADS , RESISTMICES 




Figure 2.2 LRFD Design Approach 

The LRFD Approach Has The Following Advantages: 

• It accounts for variability in both resistance and load. 

• It provides more consistent levels of safety in the superstructure and 
substructure as both are designed using the same loads for known probabilities 
of failure. 

• Using load and resistance factors provided in the code, no complex probability 
and statistical analysis is required. 

The Limitations of The LRFD Approach Include: 

• Requires a change in design procedures for engineers accustomed to ASD. 

• Resistance factors vary with design methods and are not constant. 

• Rerequires the availability of statistical data and probabilistic design algorithms. 



20 



3. Axial Pile Capacity Prediction Methods 
3.1. Axial Loading Capacity of a Driven Pile 

The ultimate resistance of a pile, Rait (or R„-Norminal resistance), is given below: 

Ruit = Rp + Rs (3.1) 
where: pile tip resistance Rp = qpAp, 

pile side resistance Rs = Z qsi Azi a, 

qp = unit tip resistance. 

qs = unit side resistance, which is regarded as constant along segment Azi of 
the pile. 

a= perimeter of the pile's shaft. 

Ap = area of the tip of the pile. 
According to surveying from Iowa State (2008), the most common static analysis 
method used for piles in cohesive soils is the a-method at 42% (Tomlinson, 1957; 
API, 1974). About 32% respondents claim to be using the P-method (Esrig and Kirby, 
1979), 1 1% use the CPT method (Nottingham and Schmertmann, 1988), and 9% 
follow the ^.-method (US Army Corps of Engineers, 1992). The most popular static 
analysis method for piles in cohesionless soils is the Nordlund's method at 63% 
(Nordlund and Thurman, 1963). About 40% of the respondents use the SPT method 
(Meyerhof, 1976/1981). 
Semi-empirical Methods 

a-method- Total stress static method of analysis for estimating the ultimate unit side 
resistance, qs, as a function of the undrained shear strength, Su, of cohesive soil 
P-method - Effective stress method of analysis for estimating qs in soil as a function 
of the effective overburden pressure 

>b-method - Effective stress method of analysis for estimating qs in soil as a function 
of the passive effective lateral earth pressure 

In-Situ Methods 



21 



SPT-method - developed by Meyerhof (1976/1981) which correlates qs and qp with 
the SPT blow count for cohesionless soils and by Schmertmann for all soil types and 
rock 

CPT-method - developed by Nottingham and Schmertmann (1975) which correlates 
qs and qp with CPT results for all soil type soils 

Methods Based on Field Testing of Pile 

PDA Method - A method for estimating total load capacity based on monitored 
performance of driven piles and wave equation analyses 
Static Load Test - A method for estimating total load capacity based on tests 
(ASTM, 1996) representative of pile, load and subsurface conditions expected for the 
prototype piles 

3.1.1. Side Resistance in Cohesive Soil 

In cohesive soil, the side resistance of a pile is usually predicted using the undrained 
shear strength, Su, or the over-consolidation ratio, OCR. This section reviews 
different methods predicting the side resistance in cohesive soil. 

3.1.1.1. a-Tomlinson Method 

The a-Tomlinson method (Tomlinson, 1979/1995), based on total stress analysis, is 
used to relate the adhesion between the pile and clay to the undrained shear strength 
of the clay, Su and has been widely used especially in stiff clays. This method 
accounts for different pile materials (i.e., concrete, timber, or steel piles) and provides 
reasonable capacity estimates for large displacement piles. The method relies on the 
a-values, which in turn depend on the bearing embedment in stiff clay and the width 
of the pile. The ultimate unit side resistance may be taken as: 

qs = aSu (3.2) 

where: 



22 



a = adhesion factor (Fig 3.1), which depends on the bearing embedment in 
stiff clay and the width of the pile. 

Su = average undrained shear strength of the soil in the segment of interest. 




50 100 150 200 

Undrained Shear Strength, S^J(kPa) 



Concrete, Timber, Corrugated Steel Piles 


. - _ Smooth Steel Piles 




D: Smaller distance from ground surface to 


bottom of clay layer or 


pile tip 


b; Pile diameter 


(IkPa = 0.145 psi) 



Figure 3.1a Adhesion values for piles in cohesive soils (after Tomlinson, 1979) 



23 




D 5D 1DD 15D 200 

Undrained Shear Strength, Cu(kPa) 




D 50 1D0 150 2DD 26D 

Undrained Shear Strength. Cu(kf^a) 



Adhesi( 
Factor. 




J Undrained Shear Strength, (kPa) 

Figure 3.1b a factors; Tomlinson method (Tomlinson, 1995) 

3.1.1.2. a-API Revised Method (1987) 

The a-method (API- 1974) is a semi-empirical, total stress approach for 
calculating the pile skin friction using the soil undrained shear strength (Su). This 
method was mainly developed for cohesive or clayey soils. It has been used for many 
years and has proven to provide reasonable design capacities for displacement and 



24 



non-displacement piles. The a-API method is similar to the a-Tomlinson method, 
and the ultimate unit side resistance, in the same unit as Su, is taken as: 

qs = aSu (3.3) 
where: a = 0.5 v|/ ""'^ if v|/< 1.0 

a = 0.5 vi/""^^ if \|/>1.0, and max a = 1.0 

\|/ = Su / Oy, and 

= the vertical effective overburden pressure at the depth of interest. 



2.0 - 




0.5 1.0 1.5 2.0 2.5 3.0 

C, T/fl.' 

Figure 3.2 Comparison between a-factors calculated form API 1986 and 1987 (Reese, 2006) 

The a-API method is a mixed method between total stress analysis (Su) and 
effective stress analysis (ay'). It is much easier to use than the Tomlinson method. 
The a-API method has simple equations and no issue with considering other layers 
that lie above the bearing layer a thus it is easy to be automated. 

3.1.1.3. p-Burland Method (1973) 

The P-method (Burland, 1973) is a semi-empirical approach based on effective 
stresses calculated from the vertical effective overburden stress. The method was 



25 



developed to model the long-term drained shear strength. It can be used for different 
soil types such as clay, silt, sand, or gravel, and can even be used for layered soil 
profiles. According to Fellenius (1991), the beta factor (P) is affected by the soil type, 
mineralogy, density, strength, pile insulation technique, and other factors. The values 
of P range between 0.23 and 0.8, but cannot exceed 2 for over-consolidated soils as 
suggested by Esrig and Kirby (1979). The P-method has been found to work best for 
piles in normally consolidated and lightly over-consolidated soils. However, the 
method tends to overestimate the pile capacity for heavily over-consolidated soils 
(AASHTO-interim 2006). This method, suggested by Burland (1973), makes the 
following assumptions: 

- Soil remolding adjacent to the pile during driving reduces the effective stress 
cohesion intercept on a Morhr's circle to zero 

- The effective stress acting on the pile surface after dissipation of excess pore 
pressures generated by volume displacement is at least equal to the horizontal 
effective stress (Ko) prior to the pile installation 

- The major shear distortion during pile loading is confined to relatively thin zone 
around the pile shaft, and drainage of this thin zone either occurs rapidly loading or 
has already occurred in the delay between the driving and loading. 

With these assumptions Burland (1973) develop the simple equation: 



qs = K (tan 5) ay' 



(3.4) 



where: K = horizontal stress ratio 



5 = adhesion angle between soil and piles 



av' = vertical effective stress 



Taking P= K (tanS), the equation can be rewritten as: 



qs = Pcfv' 



(3.5) 



where: P = factor depended on the over-consolidation ratio OCR. 



26 



50 

Figure 3.3 p factors (AASHTO 2007) 

3.1.1.4. X-Method 

The X method, proposed by Vijayvergiya and Focht (1972), is an empirical approach 
based on the assumption that the displacement of soil caused by pile driving results in 
a passive lateral pressure at any depth and that the unit skin resistance is: 

q, = Ma'+2Su) (3.6) 

Where: 

a'+2Su = Passive lateral earth pressure 

a' = Effective vertical stress at midpoint of soil layer under consideration 
Su = Undrained shear strength of soil 

X = an empirical coefficient, which can be obtained form Figure 3.4, is pile length- 
dependent and applies over the total pile embedment depth. The value of X was 
empirically determined by examining the results attained from various load tests that 
were conducted on steel pipe piles in cohesive soils, and thus, this method is more 
accurate if used for same soil and pile conditions. 




27 



0.1 O.I 



0.4 0.1 




Figure 3.4 Coefficient for driven pile piles after Vijayvergiya and Focht (1972) 
3.1.2. Tip Resistance in Cohesive Soil 

O'Neill and Reese (1999) have developed a bearing capacity factor (Nc) to calculate 
the end bearing resistance of deep foundations in cohesive soil based on the soil 
undrained shear strength as follows: 



qp = NcSu (3.7) 

where: 

qp = Net unit end bearing resistance 

Su = average undrained shear strength in the range from 2B to 3.5B below the 
tip, and B is the diameter of the pile. 
B = Pile diameter 



28 



3.1.3 Side Resistance in Cohesionless Soil 

In cohesionless soil, the side resistance of a pile is usually predicted using the 
adhesion angle, 5, or the relative density. Dr. The adhesion angle, 5, is related to the 
internal friction angle of the soil, (p, through the volume displacement, the material, 
the shape of the pile and the roughness of the pile. This section reviews different 
methods predicting the side resistance in cohesionless soil. 

3.1.3.1 p-Bushan Method (1982) 

Bushan (1982) suggests the unit side resistance for the large-displacement piles (close 
end piles, concrete piles) is related to effective stress as: 



where: p = 0.18 + 0.65 Dr, and 

Dr = Relative density in decimals 

3.1.3.2 Nordlund Method 

The Nordlund method (Nordlund and Thurman, 1963) is a semi-empirical approach 
based on field observations from pile static load tests. It accounts for different pile 
shapes (i.e., constant diameter or tapered piles), as well as pile materials and types, 
including steel H-piles, closed and open-ended pipe piles, and timber piles, 
Monotubes and Raymond step taper piles. According to Hannigan et al. (2005), this 
method is preferred in cohesionless soils, such as sandy and gravelly soils, as the pile 
load tests used to develop the Nordlunds' design curves were conducted in sandy 
soils. Moreover, the load tests were conducted for piles with diameters (widths) less 
than 500mm (19.6 inches), which meant that the method over predicted the capacity 
for piles with widths larger than 500mm (19.6 inches). 

Nordlund Method equation for computing the ultimate capacity of pile is as follow: 



qs = pcfv' 



(3.8) 



sin(S + m) 



(3.9) 



cos 57 



29 



where: K5 = coefficient of lateral earth pressure at the depth of interest. 

5 = friction angle between pile and soil. For non-taper piles:5 < cp. 

Cf = correction factor for K5 when 8^ (p. Cf ~ 0.6 to 1 .0. 

Oy = effective over-burden pressure at the center of the layer of interest, and 

CO = angle of the pile taper from vertical. 

For a uniform cross section pile (co = 0), the Nordlund equation becomes 

q^^K^Cpa^: sin S (3.10) 



tan CO 

OLDomoLDomoirjo 

00000000000 
00000000000 



7 
6 
5 
4 
3 
2 



































































































































































































































































































































































































































































































































































































































































































































































































































































































































-0 


.93 


m' 


m 
































-V 


= 


.09 


! m 










































































■V 


- a 


.00 


)a 


n^l 


n 
















































1 



0.0 0.5 1.0 1.5 2.0 



to (degrees) 

Figure 3.5 Design curve for evaluating K5 when (j) = 25(after Nordlund, 1979) 



30 



tan 0) 



oinoi/iounoLnoino 

OOOOOO-^T-T-i^-i- 
OOOOQOOOOOO 

ooooodooooo 













































































































































































































































































































































































































































































































































































































































































































































































































































































V- 


.0. 


93 hi'l 


n 




































































v = 


0. 


}93 




'm 
































0. 


309 






































3 m In 



































































































0.0 0.5 1.0 1.5 2.0 



(u (degrees) 

Figure 3.6 Design curve for evaluating Kg when ()) = 30 (after Nordlund, 1979) 

tan ca 

or^ii30Jor^u:>cjor^LD 

OOC3C3C3C3'— 1— T— T— 
OOOOOOOOOOO 

ooooooooooo 



Ks 6 

4 



1.15— 























































































































































































































































































































































































































































































































































































































































































































































— ^ 












































= 


93 


T,'l 


•n 
































-V 


= 


09 




Im 
































~v 


= 


00 


■3 1 




1 







































































































0.0 0.5 1.0 1.5 2.0 

0) (degrees) 

Figure 3.7 Design curve for evaluating K5 when dp = 35(after Nordlund, 1979) 



31 



tan (0 



20 



15 



oi^mcjoh-iflojoi^m 

oooo<::jo->-->-i--<-->- 
ooooooooooo 
ociooooooooo 



Ks 10 



4.30— 
3.00— 
1.70— 

























































































































>— 




























































































































































































































































































































































































































































































































V 




)3 


n'/r 


1 
































V 


.0. 






■rvi 

m 
































V 




)09 


3 tT 








































i 




































1 






















1 



0.0 0.5 1.0 1.5 

0) (degrees) 



2.0 



Figures. 8 Design curve for evaluating K5 when ()) = 40 (after Nordlund, 1979) 

8/(p 



0.Z5 



0.20 



Volume, ^"^^ 

0.05 



0.00 



































































































































































































































































































— ■ 


































































G 




























































































































































































































































































































































































































































































































































































































































































f 























































































































































































































































































0.00 0.25 0.5O 0.75 1.00 1.25 1.S0 

a. Pipe piles d. Raymond step taper piles 

b. Timber piles e. Raymond uniform taper piles 

c. Concrete piles f H piles 
g. Tapered portion of monotube piles 

Figure 3.9 Relation §/(j) and pile displacement (after Nordlund, 1979) 



32 



1.5 



1.0 



Correction 
Factor, Cp 



0.5 



0.0 

















































































































































5/(| 




1 


4 
















































1. 


2 




































































































9- 












































n 


R 




















































































































































-0: 


r 
















































-s. 


4- 




















































































































































-0; 























































10 



20 30 

(degrees) 



40 



50 



Figures. 10 Correction factor (Cf) for Kg (after Nordlund, 1979) 

3.1.4. Tip Resistance in Cohesionless Soil--Thurman Method 

From bearing capacity theory, Thurman related the unit tip resistance in sand 

with effective stress as: 

qp = atN'qav' (3.12) 
where: at = dimensionless factor 

N'q =bearing capacity factor 

Ov' = effective overburden pressure at the pile tip. ay' is limited to 
150 kPa (tip resistance reaches a limiting value at some distance below 
the ground), 

qp also has a limit as shown in 
N'q is very high at high internal friction angles (N'q>250 when (p>42°). 
Therefore, some software, e.g. DRIVEN (FHWA, 1998) recommends the limit of 
only 36° for cp. 



33 



«l 

Coefficient 



1.0 

0.4 
0.3 

0.2 
0.1 



D = Embedded Pile Length 
b = Pile Diameter or Width 

























































































































D 


It 


F 


tati 














































































































2 


) 






















































3 


) 


























































4 


) 





















































15 20 25 30 35 
^ (degrees) 



40 



45 



Figure 3.1 1 aj coefficient (FHWA--DRIVEN, 1998) 

1,000 



100 

Bearing 
Capacity 
Factor, N'p 

10 




15 20 25 30 35 40 45 



if (degrees) 

Figure 3.12 Bearing capacity factor Nq'(FHWA--DRIVEN, 1998) 



34 



40,000 




30 35 40 45 

Angle of Internal Friction, ^ (degrees) 

Figure 3.13 Relationship between Maximum Unit Pile Toe Resistance qL(kPa) 
and Friction Angle for Cohesionless Soils (Meyerhof, 1976/1981). 

3.1.5. Empirical Methods 

3.1.5.1 Meyerhof Method for Piles in Cohesionless Soil 

The SPT-Meyerhof method (Meyerhof, 1976/1981) is an empirical approach for 
calculating the pile capacity based on SPT tests conducted in cohesionless soils such 
as sands and non-plastic silts. According to the FHWA-LRFD reference manual 
(2007), the SPT method should be only used for preliminary estimates of the pile 
capacity, not for final design recommendations. This is due to the non-reproducibility 
of SPT N-values and simplified assumptions contained in the method. Meyerhof 
(1976) reported different correlations and provided some limitations on shaft and tip 
resistance according to the pile type (displacement or non-displacement pile). 
• Meyerhof original paper (Meyerhof, 1976/1981) 

qs = kN6o(kPa)< lOOkPa (3.13) 



35 



qp = 0.4 NeotD/B (bar) 

qp < 4 Neot in sand and qp < 3 Neot in silt. 



(3.14) 



• ASHTO provision (AASHTO 1996/2007) 



qs = ki N6o(kPa)< 100 kPa 

qp = 0.38 Neot' D/B (bar) 

qp < 4 Neot' in sand and qp < 3 Neot' in silt. 



(3.16) 



(3.15) 



• Bowles (Bowles, 1996) 

qs = kN'6o (kPa)< 100 kPa 



(3.17) 



qp = 0.4 N60(8+3B)' D/B < 3.8 N60(8+3B)' (bar). (3.18) 
• U.S. Army CORPS of Engineers, 1992: 



where: k = 2 or 1.9 if use AASHTO for concrete piles and close end pipe piles 
k = 1 or 0.96 if use AASHTO for H piles, open end pipe piles 
Neo = uncorrected blow count and N'eo = corrected blow count 
Neot = uncorrected blow count near the pile tip 
Neot' = corrected blow count near the pile tip 

N60(8+3B) = uncorrected N in the depth of 8B above tip and 3B below tip 
N6o(8+3B)' = corrected N in the depth of 8B above tip and 3B below tip 
D = the embedment of the pile in cohesionless soil 
B = the diameter or width of the pile cross-section 

3.1.5.2 Schmertmann Method for SPT 

The SPT-Schmertmann method (Lai and Graham, 1995) is an empirical approach 
based on SPT N-values, which is applicable in sand, clay, and mixed soils. This 
method is conservative, as it ignores the shaft resistance when the N-value is less than 
5 blows/ft, and also limits the N-value to 60 blows/ft. The correlations used for 
calculating the skin friction for different piles and soil types are presented in Table 
3.1. It is clear from Table 3.1 that all the correlations depend on the uncorrected SPT 



qp = 0.38 N60(8+3B) D/B < 3.8 N60(8+3B) 



(3.19) 



36 



N-values. The procedure of the Schmertmann method for SPT described below. First 
of all, the SPT blow count N is adjusted as shown below: 

If N < 5 then N = (ignores side resistance in weak soil) 

If N>60 then N = 60 (limit on side resistance) 

Table 3.1 Side resistance-Schmertmann method for SPT 



Ty- 


Description 


Ultimate unit side resistance qs(KPa) 


pe 


Concrete 


Steel H piles 


pipe piles 


1 


Plastic clay 


0.0478N(110-N) 


0.0359N(110-N) 


18.58+20.931nN 


2 


Clay-silt-sand 
mixtures 

Very silty sand, silts 


0.0418N(110-N) 


-2.174+3. 16N- 0.044N^ 
+2.36x10'^ 


23.27+14.081nN 


3 


Clean sands 


1.82N 


l.llN 


5.55+14.561nN 


4 


Soft limestone, very 
shelly sand 


0.96N 


0.73N 


1.72+12.831nN 



At any point A, the unit tip resistance is 

_ weighted average of q 8BaboveA + weighted average of q 3.5BbelowA 
qp@A 

The weighted average of qp is based on values calculated from Table (3.2) 



Table 3.2 Tip resistance-Schmertmann method for SPT 



Type 


Description 


Ultimate unit end bearing qp (KPa) 


Concrete and H piles 


Pipe piles 


1 


Plastic clay 


67 N 


0.46 N 


2 


Clay-silt-sand mixtures 
Very silty sand, silts 


153 N 


92 N 


3 


Clean sands 


306 N 


126 N 


4 


Soft limestone, very shelly sand 


345 N 


184 N 



For concrete and H piles, the mobilized tip resistance is expected to be one third (1/3) 
of the ultimate tip resistance. For pipe piles, the mobilized tip resistance is expected 



37 



to be one half (1/2) of the ultimate tip resistance. The ultimate resistance is only fully 

mobilized when the bearing embedment is sufficient, i.e. Da = Dc 

where: Da = actual bearing embedment, and Dc = critical bearing embedment 

Table 3.3 Critical depth ratio—Schmertmann method for SPT 



Soil Type 


Description 


Critical depth ratio (Dc/B) 


1 


Plastic clay 


2 


2 


Clay-silt-sand mixtures 
Very silty sand, silts 


4 


3 


Clean sands N = 12 or less 


6 




N = 30 or less 


9 




N greater than 30 


12 


4 


Soft limestone, very shelly sand 


6 



If Da < Dc and the bearing layer is stronger than the overlying layer, then: 

<lp=qLc+^{qT-qLc) 



f, 



f. 
(It 



(lic+^i^T-^Lc) 



If Da > Dc and the bearing layer is stronger than the overlying layer, then: 



I ioLC-D 



I CD 



[^iC+0-5(^CD-^ic)] 



(3.20) 
(3.21) 

(3.22) 



where: qp = Corrected tip resistance 

qLc = Unit tip resistance at layer change 

qj = Uncorrected unit tip resistance at pile tip 

fi = Corrected side resistance in the bearing layer 

fio= Uncorrected side resistance in the bearing layer 

fiLC-D = Corrected side resistance between the top of the bearing layer 

and the critical depth 

fioLC-D= uncorrected side resistance in the bearing layer from the top of 
the bearing layer to the critical depth 



38 



qcD = uncorrected unit tip resistance at D 



Weak layer 



Weak layer 



LC 



LC 



D 



Da 



Strong layer 



Da 



Strong layer 



Dc 



Dc 



T 



Figure 3.14 Corrected side and tip resistance 



3.1.5.3 Nottingham and Schmertmann Method for CPT 

Nottingham and Schmertmann (1975) developed an empirical approach for calculating the 
pile capacity based on the CPT, which is applied to cohesive and cohesionless soils. 
Correlations to CPT provide accurate pile design capacities, especially with driven piles. 
Moreover, it provides continuous readings for the soil profile and can take the effect of 
different soil layers into consideration. The cone penetration resistance, qc, is used to 
determine the tip resistance of piles and sleeve friction, fj, is used to determine the 
skin friction resistance. 

The ultimate tip resistance of piles may be taken as: 



where: 

- qci = the average qc over a distance of yD below the tip (path a-b-c); sum qc 
values in both the downward (path a-b) and upward (path b-c) directions; use 
actual qc value along path a-b and the minimum path rule along path b-c; 
compute qci for y value from 0.7 to 4.0 and use the minimum qd value obtained 



39 



- qc2= average qc over distance of 8D above the pile tip (path c-e); use minimum 
path rule as for path b-c in qd, computation; ignore any minor "x" peak 
depression if in sand but include in minimum path if in clay 




Figure 3.15 Tip resistance computation procedure—Nottingham 1975 
Similarly, the nominal side resistance of piles may be taken as: 



f L ^ ^2 

— — f a h. + f a h + 

Q r-v J SI SI I / 1 J SI SI I 



(3.24) 



Where: 



Ks_c= correction factor, Kc for clays. Kg for sands from figure (3.16a, 3.16b) 
Li=depth to middle of length interval at the point consider (mm) 
Di=pile width or diameter at the point considered (mm) 



40 



fsi= unit local sleeve friction resistance at the point considered (MPa) 
asi=pile perimeter at the point consider (mm) 
hi= length interval at the point considered (mm) 

Ni= number of interval between the ground surface and a point 8D below the 
ground surface 

N2=number of interval between 8D below the ground surface and the tip of the 
pile 

For a pile of constant cross-section (nontapered) equation (3.24) can be written as: 



^yL.f.h+a y f.h. 

Q j-^ / J I J S! I S / 1 J SI I 



(3.25) 



10 



K lor Steel Pipe Piles 
1.0 2,0 



D/b 



20 



30 



40 

































- 
































































































f 






















M 
































\ 


















h 






El 




ric 


il 






















_ P( 


nalrc 


m 


Jter 






























































































■ 1 






! 
















ICfl 


an 


ic: 
























fietrfl 


n( 


Iter 






— 1 












































i 
























1 






1 








1 i 







K for Square Concrete Piles 
3.0 0.0 1.0 2-0 




- 10 



D/b 



40 





— r- 
































J 
















/- 


















■ 
















































f 
















V- 








V 












E 


ec 


ric 


al 


or 


■ 


1 


P 


er 


elrorhel 




1 
















1 






































.\ 


\ 




■ 






1 


4e 


;h 
atr 


an lea 




P 


eti 








- 
















1- 









Figure 3.16a Ks ratio in cohesionless 



Tjpe of piles 


Cf 


Precast concrete 


0.012 


Timber 


0.018 


Steel displacement 


0.012 


Open eutl steel pipe 


O.OOS 



41 



a' 

















M 1 1 1 1 1 1 1 




















(IkPa =0.145 psi) 







































































i 








Tr 
























i 


icret 




V 


iber 


P 


les 








































































-r 






















Era 







































































































































50 100 150 200 

Penetrometer Sleeve Friction, fs (kPa) 

Figure 3.16b Kc ratio in cohesive soil 



Table 3.5 Methods for calculating axial loading capacity of a driven pi 


e 


Soil Type 


Methods 


Side resistance 


Tip resistance 


Parameters 
required 


Cohesive Soil 


a-Tomlinson 
(Tomlinson, 1980/1 995) 


qs = aSu 


qp = 9 S, 


Su 


a-API 
(Reese et al, 1998) 


Su 


P in cohesive 
(AASHTO, 1996/2000) 


qs = Pa' 


OCR 


X (US Army Corps of 
Engineers, 1992) 


q, = ^(a'+2S„) 


Su 


Cohesionless 
Soil 


P in cohesionless 
(Bowles, 1996) 


Pa' 






Nordlund and Thurman 
(Hannigan et al, 1995) 


,sin(^ + a7) 

C0S5T 


qp = tttN'q a' 


(p 


Meyerhof SPT 
(Meyerhof, 1976/1981) 


qs = kN 


qp = 0.4D/BN' 


SPT-N value 


Cohesion/cohe 
sionless Soil 


Schmertmann SPT (Lai 
and Graham, 1 995) 


qs = flinction(N) 


qp = fn(N) 


SPT-N value 


Schmertmann CPT 

(McVay and 
Townsend, 1989) 


qs = flinction(fs) 


qp = fn(qc) 


qc, fs 



42 



3.2 Axial Loading Capacity of a Drilled Shalf 

The ultimate resistance of a pile, Ruit (or Rn~NorminaI resistance), is given below: 

Ruit = Rp + Rs (3.26) 
where: pile tip resistance Rp = qpAp, 

pile side resistance Rs = Z qsi Azi a 

qp = unit tip resistance. 

qs = unit side resistance, which is regarded as constant along segment Azi of 
the pile. 

a = perimeter of the pile's shaft, and 
Ap = area of the tip of the pile. 

3.2.1 Side Resistance in Cohesive Soils 

3.2.1.1 FHWA method 

The following equation gives the a method for the evaluation of the skin (side or 
frictional) resistance of drilled shafts in cohesive soils at depth z: 

q,=as^, (3.27) 

where 

= ultimate skin resistance at depth z 
5*,, = undrained shear strength (cohesion) at depth z 

a = empirical adhesion factor depends on undrained cohesion. 

The values of a varies from 0.3 to 1.0 and the following best-fit functional 
relationship (Eq. 3.28) shows that the a values decrease with the increasing 
undrained shear strength (Kulhawy and Jackson (1989): 

a = 0.21 + 0.25^ (3.28) 

where = atmospheric pressure. In other words, the soft normally consolidated clay 
has a higher a value than the hard overconsolidated clay. 



43 



O'Neill and Reese (1999) recommended the following equation for the average value 
of a : 

S.. 



a = 0.55 for ^<1.5 

Pa 



(3.29) 



and 



a = 0.55-0.1 



-1.5 



for 1.5<^<2.5 

Pa 



(3.30) 



For the case of 5*,, /p^> 2.5 , skin resistance should be calculated as the methods for 
cohesive intermediate geomaterials (O'Neill and Reese, 1999) 
The total skin resistance, , is equal to the peripheral area of the shaft multiplied by 
the unit side resistance shown as follows: 



where 



Q^=;rDY,c(-S:L (3.31) 
D = pile diameter 

r = thickness of layer i, where the values of a and are constants. 





1 




1 

J 







I Top Five Feet (1.5 Meters) 
' Noncontf itjuting for 
I Compression Loedlng 



Top Five Feet (1.5 Meiers) 
; Noncontributing tor Both 
Compression and UpJill 



D 



I Bottom One Diameter 
I NoncontribJting in 
^ Compression Loading 




Bottom One Shaft Diameter 
o( Stem Noncomributinfl 



P^jptiery ot Bell 
Noricontributing 



Belled Shian in Compression 



Figure3.17 Explanation of Portions of Drilled Shaft Not Considered in 
Computing Side Resistance in Clay (O'NeiUl and Reese, 1999) 



44 



The peripheral areas over which side resistance in clay is computed are show in 
Figure 3.17. The upper portion of the shaft is excluded for compression to account for 
soil shrinkage in the zone of seasonal moisture change. The lower portion of shaft is 
exclusion when the shaft is loaded is compression because downward movement of 
the base will generate tensile stress in soil that will be relieved by cracking of soil and 
porewater suction will be relieved by inward movement of ground water. 

3.2.2 End Bearing in Cohesive Soils 

3.2.2.1 FHWA method 

The prediction of end bearing capacity of drilled shaft in clays is much less uncertain 
than is the prediction of skin resistance (Reese et al. 2006). The equation below is 
used for calculating the net base resistance: 

Q„=A,SX (3.32) 
where = area of the base; 5*,, = an average undrained shear strength of the clay 

calculated over a depth of two time of diameter below the base (Reese et al., 2006); 

= bearing capacity factor usually taken to be 9 when the ratio LjDj^ is 4 or more 
(Das, 1999). According to O'Neill and Reese (1999), for the straight shaft, the full 
value of NI = 9 is obtained when the base movement of about 20% of Z) . If the base 

movement is unknown, the bearing capacity factor A^* can be calculated by (Reese et 
al, 2006): 

iV; =1.33(ln/,. + l) (3.33) 
where /,. is the rigidity index of saturated clay under undrained condition: 

I,=— (3-34) 
35„ 

where is undrained Young's modulus. If is not measured, N] and can be 
estimated from: 



45 



Table 3.6 Values of /,. and (Reese, et al, 2006) 







K 


24 kPa (500 Ib/ft^) 


50 


6.5 


48 kPa(1000 1b/ft^) 


150 


8.0 


> 96 (2000 Ib/ft^) 


250-300 


9.0 



3.2.3 Side Resistance in Cohesionless Soil 
3.2.3.1 FHWA method 

The following equation is used to calculate the ultimate unit skin resistance in sand at 
depth z: 

q^=Ka'JanS (3.35) 

Where: 

-K = a parameter that includes the effect of the lateral pressure coefficient and a 
correlation factor - cr' = vertical effective stress in soil at depth z 

-S = friction angle at the interface of pile surface and soil. 

The total side resistance calculated from the summation of each layer of unit side 

resistance multiplied by perimeter and layer thickness is shown as follow: 

= ttDJ^ K'ct'; tan (p[.L. (3.36) 

O'Neill and Reese (1999) suggested the expression for the ultimate unit skin 
resistance in sand: 

= ^o-; < 200 kPa (3.37) 

and 

Q^^nDY,p'a% (3.38) 

Where: In sands 

y9 = 1.5-0.135z(/0°',(0.25<y9<1.20)forSPT ^ ,^>\5 (blows/ft) 



46 



P = {N,J\5)[\.5-0.U5zifty') for SPT N,,<\5 (blows/ft) 

In gravelly sands or gravels when, use the method for sands if 
N,, < 15 (blows/ft) (O'Neill and Reese, 1999) 



Table 3.7 ^ for Gravelly sands and Gravels (Rollins et al, 2005) 



Percentage Gravel 


/3 


Smaller than 25% 


y9 = 1.5-0.135z°'; 0.25 <;5< 1.20 


Between 25% and 50% 


y9 = 2.0 - 0.06 15z'' ''; 0.25 <y9< 1.80 


Greater than 50% 


^9 = 3.46 °°'"'-'; 0.25 <;^< 3.0 



3.2.3.2 Reese and Wright method 

Reese and Wright (1977) proposed a semi-empirical method to estimate the unit skin 

friction (qs) and unit bearing (qp) for drilled shafts founded in sands using 

uncorrected SPT blow count, N 

Unit skin friction for, qs, for sands: 

For N<53 qs = 0.0028N (Mpa) 

For 53<N<100 qs= 0.0002 l(N-53) + 0.15(Mpa) 

In the case of multiple soil layer, i.e. sand and clay, the FHWA approach for clay 

3.2.4 End Bearing in Cohesionless Soil 
3.2.4.1 FHWA method 

According to O'Neill and Reese (1999), tip resistance for cohesionless soil with blow 
count Ngpj^ < 50 (blows/ft) can be found by foUowing equation: 

q^, = 51.5Nspr kPa < 2.9 MPa (3.39) 

When N^pj, > 50 (blows/ft), should be calculated according to equations for 

intermediate geometerials (IMGs) as: 



47 



^,=0.59 



60 



a 



(3.40) 



Where: pa = atmospheric pressure 

a'v = vertical effective stress at the tip elevation of the shaft (MPa) 
N60 =should be limited to 100 in Eq if higher values are measured 

3.2.4.2 Reese and Wright method 

Unit end bearing, qp for sands: 

For N < 60 qp = 0.064*N (Mpa) 

ForN>60 qp=3.8(Mpa) 
N: is the uncorrected Ngpt value 

3.2.5 Side Resistance in Rock 

Drilled shaft in rock subject to compressive loading shaU be designed to support 
factored load in: Side-wall shear comprising skin friction on the wall of the rock 
socket; or End bearing on the material below the tip of the drilled shaft or a 
combination of both. For the drilled shafts socket in to rock, shaft resistance. In MPa, 
may be taken as (Horvath and Kenney 1979) 



q..=0.65a,pAqJpy'<l.SpAf\/pS' (3.41) 

Where: 

qs = uniaxial compressive rock (MPa) 
Pa= atmospheric pressure 

ttE = reduction factor to account for jointing in rock as provide in table (3.6) 

f c= concrete compressive strength (MPa) 

Table 3.8 Estimation of «£ (O'Neil and Reesse, 1999) 



Em/Ei*"^ 


OLE 


1.0 


1.0 


0.5 


0.8 



48 



0.3 


0.7 


0.1 


0.55 


0.05 


0.45 



(a) Em: rock mass modulus Ei: intact rock modulus 
3.2.6 Tip Resistance in Rock 

End bearing for drilled shafts in rock may be taken as follows: 

• If the rock below the base of the drilled shaft to depth of 2. OB is either intact or 
tightly joints, i.e., no compressible or gouge filled seams and the depth of the 
socket is greater than 1.5 B 

q„=2.5qu (3-42) 

• If rock below the base of the shaft to a depth of 2. OB is joints have random 
orientation and the condition of joints can be evaluated as: 



(3.43) 



Where: s, m= fi-actured rock mass parameters and are specified in table () 
qu= unconfined compressive strength of roc (MP a) 



Table 3.9 Met 


lods for calculating axial loading capacity of a drilled shaft 


Soil 
Condition 


Resistance 
Component 


Equations 


Parameters 


Cohesive Soil 


Skin 
Friction 


FHWA metliod: 
q =as 

"SZ LIZ 


a: shear strength reduction factor 

Suzi: undrained shear strength at depth z 

qsz: ultimate load transfer in skin friction at z 

dA: differential area of the shaft 

L: penetration depth of the drilled shaft 

below ground surface 


End Bearing 


FHW method 

Q, = ^S^,N^ 


Nc: bearing capacity factor 

Su: average undrained shear strength of the 

clay between the base and a depth of 2B 

Ir: rigidity index of the soil 

Es: Young's modulus of the soil 


Cohesionless 
Soil 


Skin 
Friction 


FHWA method: 

q^ = pa[ < 200 kPa 


o' : vertical effective stress in soil at depth z 
z: depth below the ground surface 



49 







f3 = \.5-Q.U5z{ftf\ 
(0.25<;5<1.20)if TVgo >15 

P^{N,J\5)(\.5-0.\2>5z{ftr) 

if iVgo < 15 (blows/ft) 

Reese and Wright method: 
For N<53 qs = 0.0028N (Mpa) 
For53<N<100 qs = 0.0002 l(N-53) 
+ 0.15(Mpa) 




End Bearing 


FHWA method: 

= 57.5Nspj kPa < 2.9 MPa 

when N^pj, < 50 

p 

q^=0.59 N,, ^ a\. 

when Ngpj. > 50 
Reese method: 

For N < 60 qp = 0.064*N (Mpa) 
ForN>60 qp = 3.8(Mpa) 


Nspt: average blow count from the zone 
between the base and a depth of 2B 


Rock 


Skin 
Friction 


q,,=0.65aj,p^(qj pj"' 
<^-^PAf\IPar 


qs = uniaxial compressive rock (MPa) 

pa= atmospheric pressure 

aE = reduction factor to account for jointing 

in rock as provide in table (3.6) 

f c= concrete compressive strength (MPa) 


End Bearing 


qp = 4s+^l{m4s +s ^„ 





3.3 Piles Dynamic Analysis 



50 



3.3.1 The Case Method 

Static pile bearing capacity can be calculated by Case method using following 
equation: 



Where: 



F^, is measured force at time 



is measured force at time t^+2LI c 



Uf^y is measured velocity at time 

Uj^2 is measured velocity at time t^+2L/c 

is Case damping 
Z: Impedance 

The impedance, Z, of a pile is a function of the dynamic modulus, E, the wave speed, 
c, and the pile cross-sectional area, A. 

FA 

Z = — (3.45) 

c 

The wave speed can be calculated by the following equation 

c = — (3.46) 

t 

Where: L: Length of the Pile 

t: Time Required for the Pulse to Travel Twice the Pile Length 
The dynamic modulus of the pile material, E, is presented in the following equation 

E = pc' (3.47) 
Where: p : mass density of the pile material 
c: the wave speed. 

Since the Case damping constant is assumed, the static capacity will be known from 
above equation. 



51 



3.3.2 The Energy Approach 

The Energy Approach method or "Paikowsky" is a simpUfied energy approach 
formulation for the prediction of pile resistance based on the dynamic measurements 
recorded during driving. The basic assumption of the method is an elasto-plastic load 
displacement pile-soil reaction. The Paikowsky method uses as input parameters the 
maximum calculated transferred energy and maximum pile displacement from the 
measured data together with the field blow count. Equation () presents the solution for 
the dynamic pile capacity Ru (Paikowsky, 1994). 

Set + ^^ ^ 

2 

Where: Rui maximum pile resistance 

Emax: measured maximum energy delivered to the pile 

Dm:ax: mcasurcd maximum pile top displacement 
Set: permanent displacement of the pile at the end of the analyzed blow, or 
1 /measured blow count. 

3.3.3 The Signal Matching 

The Case Pile Wave Analysis Program (CAPWAP) is a computer program that 
combines the wave equation's pile and soil model with the Case method of forces and 
velocities from PDA. The CAPWAP solution includes the static total resistance, skin 
friction and toe bearing of the pile, in addition to the soil resistance distribution, 
damping factors, and soil stiffness. The program calculates acceleration, velocities, 
displacements, waves up, waves down and forces at all points along the pile. The 
procedure used by CAPWAP includes inputting the force trace obtained from PDA 
and adjust the soils parameters until the velocity trace obtained from PDA can be 
recreated. It should be noticed that the opposite procedure (i.e. input velocity trace 
and generate the force trace) can also be performed. When the match obtained is 
unsatisfactory, it is necessary to modify the soil parameters, until reaching a 



52 



satisfactory match results. The process of running CAPWAP is considered an 
iterative one. 

3.4 Static Load Test 

Static Load Tests (SLTs) accurately measure the actual pile behavior under axial 
vertical compressive loading and characterize the load-settlement relationship at the 
pile head. Load testing is the most definitive method for determining the nominal 
capacity of a pile. Testing a pile to failure provides valuable information to the design 
engineer and is recommended for design verification purposes. In difficult soil and 
bedrock conditions, the SLT results are the only means of identifying the actual pile 
capacity and also helps in generating databases to find the resistant factors. 
3.4.1 ASTM Procedures 

The American Standard for Testing and Materials (ASTM) have four static load 
test procedures including the standard loading procedure, cyclic loading, quick load 
test, and constant rate of penetration. 

3.4.1.1 Standard Loading Procedure 

The standard ASTM method calls for piles to be loaded to 200% of the 
anticipated design load, unless failure occurs first. The pile shall be loaded in 
increments of 25% of the total test load. Each load increment will be held until the 
rate of settlement is not greater than 0.25 mm/hr (0.01 inches per hour) but no longer 
than two hours per increment. In the event the pile has not failed, hold the total load 
on the test pile between 12 and 24 hours until the settlement is not greater than 0.25 
mm/hr (0.01 inches per hour). After the settlement rates have been satisfied, remove 
the load in decrements of 25% of the total test load with one hour between 
decrements. 

3.4.1.2 Cyclic Loading 



53 



The pile is loaded in a series of four cycles. The first cycle is loaded in increments 
of 25% of the total design load up to 50% and each load increment is held for one 
hour. At 50% the pile is unloaded in decrements of 25% until the entire load is 
removed from the pile with 20 minutes between decrements. Cycles two, three, and 
four are loaded to 100%, 150%, and 200%, respectively in increments of 50% of the 
total design load. Each load increment is held for one hour during each cycle. Once 
the maximum load is reached per cycle, the pile is unloaded to zero in decrements of 
50% of the maximum applied load with 20 minutes between each unloading. 

Tiine(Hrs) 



250 



•a 

at 
e 



e 



225 -■ 
200 - 
175 - 
150 - 
125 -■ 
100 - 
75 - 
50 - 
25 - 



] 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 

1 ■ ■ . I 1 ^ I , ■ . I ■ ■ ■ I ■ . . ; , , , I ■ . . I ■ ■ ■ I ■ . , t ■ ■ ■ I ■ , , I , . . I ■ ■ ■ I ■ ■ ■ I , , , I ■ ■ ■ I ■ 



Note: The Quick Test is carried out 
until failure or until the capacity of 

the Loading apparatus is reached. 



12 io 14 hii 
jrirailu« do(» 
not take place 



Standard Loading Procedure 
Cyclic Loading Procedure 
Quick Load Test 

■n — - 



L. 



I I I I I I 



I I I'l I I'l I I I I I I I I I I I I I I I I I r' I I I I I I I I I I I 

100 200 300 400 500 600 700 800 900 1000 

DuratioD {mln) 

Figure 3.18 Static pile load testing procedures according to ASTM (Paikowsky, 2004) 

3.4.1.3 Quick Load Test Method for Individual Piles 

The load is applied in increments of 10 to 15% of the design load with a 
constant time interval of 2.5 minutes between loading increments. Load increments 
are added until continuous jacking is required to hold the test load or until the 



54 



specified capacity of the loading device is reached. After one of these criteria is 
reached, the load is held for five minutes and the full load is removed trom the pile. 

3.4.1.4 Constant Rate of Penetration 

The pile is loaded at a constant rate of penetration 0.3 to 1.3 mm/min (0.01 to 
0.05 in/min) for cohesive soils or 0.8 to 2.5 mm/hr (0.03 to 0.1 in/min) for granular 
soils. The pile is continually loaded until no further increase in load is necessary for 
the constant rate of penetration of the pile under the predetermined rate or the 
capacity of the pile is reached. If the pile continues to settle under the constant load, 
the load is held until the pile has moved at least 15% of the pile diameter and then the 
pile is unloaded completely. If maximum capacity of the pile is reached before failure, 
the total load is released. 

3.4.2 Vietnamese Procedures 

Most of static load data from Vietnam use the same standard load procedure from 
ASTM and cyclic load procedure but in Vietnam the pile is loaded in a series of two 
cycles instead of four cycles in ASTM. The first cycle is loaded up to 100% of the 
anticipated design load in increments of 25% and each load increment is held for one 
hour. At 100% the pile is unloaded in decrements of 25% until the entire load is 
removed from the pile with 20 minutes between decrements. Cycles two is loaded to 
200%, respectively in increments of 25% of the total design load. Each load 
increment is held for one hour during each cycle. Once the maximum load is reached 
per cycle, the pile is unloaded to zero in decrements of 50% of the maximum applied 
load with 20 minutes between each unloading. 

3.5 Interpretation from Static Load Tests 
3.5.1 Davisson's Method 

The Davisson method (Davisson 1972) is one of the most popular methods and it 
is based on the elastic compression of the pile. This method takes into account the 
elastic shortening of pile under the axial load, the required relative movement 0.15 in 



55 



between the soil and the pile for full mobilization of side friction, and the amount of 
tip movement (1/120* of pile diameter in inches) for mobilization of tip resistance. 
The ultimate load of a pile can express in the following form: 



120 Aj,Ej, 



(3.49) 



Load Q J, 




0.004 Lr + B/1 20 Ql.ii*L/ApE(, S 6 ttleiTI 6 n t IV 

Figure 3.19 Graphical representation of Davisson's criterion 

where: 

Quit= ultimate load 

Wuit=settlement ( in the same unit as Lr) observed for the pile when Q=Quit 
Li = reference length = lm 

B= pile diameter (or width) in the same units as Lr 
Ap = cross sectional area of the pile (in unit of Lr) 

Ep = pile Young's modulus (in units consistent with those of load and length) 

L = pile length in the same unit as Lr 
Davisson's criterion was used in the NCHRP report-507 by Paikowsky et al. 
(2004), and was found to perform best overall. One of the main advantages of this 
method is that it is an objective method and it can be used as an acceptance criterion 



56 



for the static load test. However, Hannigan et al. (2005) supposed some limitations of 
this method, as it under-predicts the pile capacity for piles with diameters larger than 
24 inches. 

3.5.2 The Limited Total Settlement Methods 

The Limited Total Settlement methods, A = 25.4 mm and A = O.IB (Terzaghi, 
1942), define the failure load as the load corresponding to settlements of 25.4 mm and 
O.IB, respectively, where B is the diameter of the pile. These methods are not 
applicable in many cases. For example, the elastic compression for a very long steel 
pile often exceeds 25.4 mm and/or O.IB without inducing any plastic deformation in 
the soil. 

3.5.3 DeBeer's Method 

DeBeer (1970) defines the failure load as the load corresponding to the 
intersection of two distinct slopes created by the load-settlement data plotted using 
logarithmic scales. The two slopes are especially visible for piles that experience 
plunging failures, yet when using DeBeer's method piles that undergo local failures, 
the result may be a range of values, such as illustrated here 

Log Q 
Log Qjit 4 




Figure 3.20 Graphical representation of DeBeer method 



57 



3.5.4 Chin's Method (1970) for Estimate the Ultimate Load of Piles from the 
Test not Carried to Failure 

It is usually very expensive and often impractical to extend a load test on a large 
pile or a pile group until collapse .The ultimate load of a pile can be obtained from the 
results of a load test without having to load the pile to failure. The Chin's method 
(1970) is base on the results of an experiment study of the shear deformation 
characteristics obtained from shear box and triaxial tests and from the tests carried out 
with the model piles in both the field and in laboratory. The load test show that the 

deformation and load relation ship is hyperbolic and the plot of ^^^^f^^^^^^^^^ 

P{load) 

versus ^{deformation) is liner and the inverse of this line therefore gives the ultimate 
value ofloadP(Chin 1970) 

The pile load-settlement (Q-w) curve can be express by following equation: 

Q = ^— (3.50) 

a+bw 

Where a and b are constant with very specific physical meanings 



Load Q 



1/a , 



IV 1 

Q * 



1/b 



Figure 3.21a Load-settlement curve 



w 



Figure 3.21b Replotted results for 
determination of Ci and Ql 



58 



If we rewrite equation (3.50) as 

w 1 

Q = ^— = (3.51) 

a + bw 

w 

As the settlement w approaches infinity, Q approaches 1/b. And by definition the load 
at infinite settlement is the ultimate load Quit so it follows that 

b 



If dividing Q/w, we obtain the equation for the pile head stiffness K, 



K,=^ = — — (3.53) 
w a + bw 

As w=0, =— is the initial pile head stiffness 
a 

n • • -11 1 1^1-1 wideformation) 

The nowmg equation will be used tor plotting the versus w 

PQoad) 

— = bw + a = w + (3.54) 

Q Quit ^i(w=o) 

From plotting we find out the Quit of static load test of pile. 

3.6 Soil Properties Correlated from Insitu Tests 

Most of the static methods directly or indirectly utilize the soil shear strength 
parameters when calculating the capacity of pile foundations. These parameters could 
be determined using laboratory tests or correlations to field tests such as the SPT or 
CPT. From the Iowa's survey result ( 2008), 94% of the respondents claimed to be 
using the Standard Penetration Test (SPT), 52% use the Cone Penetration Test (CPT), 
16%) follow the Vane Shear Test (VST), and around 20% perform other methods. 
The survey confirmed that the majority of respondents depend on SPT or CPT tests to 
determine the basic soil parameters. 

The SPT has been used in correlations for soil unit weight (y), relative density 
(Dr), angle of internal friction ((j)), and unconfined compressive strength (Su). There 



59 



are several correlations between the SPT N-values and different soil parameters and 
presented in Table 3.8. According to Paikowsky et al. (2004), the best correlation for 
determining (j) in cohesionless soils is provided by Peck Hanson and Thornbum 
(1974), and it is recommended to limit (j) below 36°. The most common correlation 
used to estimate the Su from SPT is also the one provided by Terzaghi and Peck 
(1967) using the uncorrected N-values. Tables 3.7a and 3.7b after Bowles (1977) 
summarize different ranges of Dr, (j), qu and y with respect to corrected and 
uncorrected N-values, respectively. On the other hand, there are many empirical 
correlations to estimate the soil shear strength parameters from the CPT test. As 
shown in Table 3.9, the Su and (j) were mainly calculated based on the CPT cone tip 
resistance (qc), as well as the soil effective overburden pressure (a'v). According to 
Paikowsky et al. (2004), the best correlation for determining Su is by Hara (1974), 
while the correlation used by Robertson and Campanella (1983) was most commonly 
used for calculating the soil internal friction angle. 



Table 3.10a: Correlations between SPT N-values and Dr, ^, and y soil (after Bowles, 
1977)* 



Description 


Very Loose 


Loose 


Medium 


Dense 


Very Dense 


Corrected SPT N-value 


0to4 


4 to 10 


10 to 30 


30 to 50 


50+ 


Relative density, Dr 


0-0.15 


0.15-0.35 


0.35-0.65 


0.65-0.85 


0.85-1.00 


Internal friction Angle, (j) 


25 - 30° 


27 - 32° 


30-35° 


35 -40° 


38-43° 


Unit weight, y (kN/m3) 


11.0-15.7 


14.1 - 18.1 


17.3-20.4 


17.3-22.0 


20.4-23.6 



*Use 5% larger values for granular material. 

Table 3.10b: Correlations between SPT N-values and qu and y (after Bowles, 1977)* 



Description 


Very soft 


Soft 


Medium 


Stiff 


Very Stiff 


Hard 


Un-corrected 


0to2 


2 to 4 


4 to 8 


8 to 16 


16-32 


32+ 


SPT N-value 














Su (kPa) 


0-24 


24-48 


48-96 


96-192 


192-384 


384+ 


y (kN/m3) 


15.8-18.8 


15.8-18.8 


17.3-20.4 


18.8-22.0 


18.8- 22.0 


18.8-22.0 



Correlations should be used for preliminary estimates only 



60 



3.6.1 Correlations of Soil Properties from SPT 
3.6.1.1 Undrained Shear Strength Su 

Terzaghi and Peck (1967): Su/pa = 0.06 N 
Kara (1974): Su/p^ = 0.29 N° 

where: N is the uncorrected blow counts 



tO.72 



10 



5 - 



0.5 



-I 1 — I — I I I I I I 



■T 1 r 



.,0,72 



(nslSO, r^ = 0.865) 




25 clay sites In Japon 
(PISI0-9S, 0CR>l-3] 



_L 



5 10 
SPT NJ Value 



50 100 



Figure 3.22 Su-SPT N Relationships by Hara 1974 
(Kulhawy and Mayne, 1990) 

3.6.1.2 OCR for Clay 

Mayne and Kemper: OCR = 0.58 Npa / <j\ 
where: N is the uncorrected blow counts 



(3.53) 
(3.54) 



(3.55) 



61 



o 



a 

"a 



50 



20 



10 



I ' '-"I 
fissured ■ 



OCR = 0.58 Npo/^yo 
(n = ll2. r^^O.Sei, 
3.D. = 3.e2l — \ 



Jo 

1 



* i 3 fissured cloys 

' / ^ 



_L 



2 5 10 20 50 100 

SPT N Value, M Pa/o-^o (blows/ft or 305mm) 



Figure 3.23 OCR-N Relationships (Kulhawy and Mayne, 1990) 
3.6.1.3 The Effective Stress Friction Angle for Cohesionless Soil 
Peck, Hanson and Thornburn: 




28 



32* 36* 40" 

Friction Angle, ^t^. 



44< 



Figure 3.24 (p'-N Relationships by Peck, Hanson and Thornburn 
(Kulhawy and Mayne, 1990) 

Schmertmann: 



cp' ^ tan"' [N / (12.2 + 20.3 aVo/pa)] "'^^ 



(3.57) 



where: N is the uncorrected blow count, avo': vertical stress 



62 



SPT N Value, Blows/ft or 305mm 




3.6 



Figure 3.25 cp'-N Relationships by Schmertmann (Kulhawy and Mayne, 1990) 
1.4 Relative Density Dr of Cohensionless Soil 



£ 
E 

tn 
O 



01 



100 




SPT N Volue (blows/ft or 305Tnm) 



en 
tn 
<u 
w 

to 



5i 




20 40 60 80 
Relative Density. Dr (%) 



100 



Figure 3.26 Relative Density ~N~Stress Relationships 
(Kulhawy and Mayne, 1990) 



63 



Table: 3.11 Summary correlations between SPT N-values and soil parameters 



Soil 
Properties 


SPT - N value Correlation 


Reference 


9 


54-27.6 exp(-0.014N') 


Peck, Hanson and Thombum ( 1 974) 


tan' [N/ (12.2 + 20.3 u')]°-^^ 


Schmertmann (1975) 


Su (bar) 


0.06 N 


Terzaghi and Peck (1967) 


0.29 N°-^^ 


Kara (1974) 


OCR for clay 


0.5N/a'o (a'oinbar) 


Mayne and Kemper 


Dr 


Gibbs and Holtz's Figures 


Kulhawy and Mayne, 1990 



3.6.2 Correlations of Soil Properties from CPT 

3.6.2.1 Undrained Shear Strength Su 

The theoretical relationship for the cone tip resistance in clay is given by: 

Su/pa = (qc - ao) /Nk (3.58) 
where: qc= cone tip resistance, ao= total overburden stress and Nk= cone bearing 
factor. The application of classical plastic theory to this bearing capacity problem 
suggests Nk=on the order of 9 for general shear model 

3.6.2.2 OCR for Cohesive Soil - Mayne 




Figure 3.27 ap-qc Relationships (OCR = ap / a'o) (Kulhawy and Mayne, 1990) 



64 



The cone penetration test (CPT) tip resistant, qc, has been used effectively to profile 
the preconsolidation stress in clay. Figure presents the available data from 49 clays. 

OCR= 0.29 qc / a'o (3.59) 
where: qc= cone tip resistance, Oo= total overburden stress 

3.6.2.3 The Effective Stress Friction Angle for Cohensionless Soil Robertson and 
Campanella 

ct)'= tan"^(0.1+0.381og(qc/avo')) (3.60) 
where: qc= cone tip resistance 

total overburden stress 

Cone Tip Resistance, q, /p. 




Figure 3.28 cp'tc correlated from qc for NC, uncemented quartz sands 
(Kulhawy and Mayne, 1990) 



65 



3.6.2.4 Relative Density Dr of Cohensionless Soil- Jamiolkowski 



Dr 



68 



log 



qc 



0.9 + D./ 300 



where: qc= cone tip resistance, Oo= total overburden stress 

100 



80 - 



2 60 
Q 

03 



2 40 



ZO 



T 



I I I f I I I 1 1 



D,(%)-S8 [log(rz==)H] y 



TTI — rT-TT 




Sond 



• Tietno 
A Otiawo 
o Edgor 

• Hokksund 
' Hilton mines 

_j 



10 50 100 

Cone Tip Resistonce, 



500 1000 



,0.5 



Figure 3.29 Correlation between Dr and qc by Jamiolkowski 
(uncorrected for boundary effect) (Kulhawy and Mayne, 1 990) 



(3.61) 



Table 3.12 Summary Correlations between CPT and soil parameters 



Properties 


From CPT 


Reference 


9 (deg.) 


atan(0.1+0.38*Log(qc/a')) 


Robertson and Campanella (1983) 


(bar) 


( qc - c?o ) / Nk ; qc and Uo in bars. 


Kara (1974) 


OCR for clay 


0.29 qc / a'o; qc and Uo in bars. 


Mayne 


Dr 


q' 

68 log(qen) 68 ; q^n " , 

q'c = qc / Kq, Kq = 0.9 + Dr/300, qc and a'o in bars. 


Jamiolkowski 



66 



3.6.3 Soil Properties Correlated from Laboratory Tests 

For cohesive soils, Atterberg limits and their relationship to the in-situ water content 
are most commonly used for such correlations. Figure 3.30 shows one correlation 
between the Liquidity Index, LI, and the ratio of undrained shear strength to vertical 
effective stress level in triaxial compression, Su/a'vo. 

g~ 0,4 1 1 1 1 ] 1 ; [ 

^ 0.3- 

O 
3 



Ol I 1 \ I I \ I I 

12 3 4- 

Liquidity Index, LI 

Figure 3.30 Correlation between Normalized Undrained Shear Strength and 
Liquidity Index for NC Clays (after Kulhawy and Mayne, 1 990) 




67 



4. Determination of Resistance Factors by Calibration 
4.1 Calibration by fitting ASD to LRFD 

Calibration by fitting to ASD is used if the data required for the statistical analysis is 
not available. In this case, the LRFD resistance factors obtained by fitting to the ASD 
method should be only used as a benchmark to provide the same degree of safety that was 
provided by the ASD. However, this does not satisfy the LRFD reliability based 
requirements. 



Divide the LRFD equation: ORn = Z rjiyi Qiby the ASD equation: Rn =FsZQ i 
<l>Rn _ Hw.Q. .... 

From which, with r|i = 1 .0 

(/>= ^ (4.2) 

If the loads consist only of dead load Qd and live load Ql, then Eq (4.2) becomes 

r\ , r\ Yd -r^ '^Yl 

FS{Qo+Ql) FSi^ + \) ^^'^^ 

Table 4.1 shows the resistance factors, calibrated by fitting with ASD after McVay et 
al., 1998; depend on the DL to LL ratio. The DL/LL ratio could range between 1.0 and 
4.0 for bridge structures depending on the bridge span and other factors. Barker et al., 
(1991), recommended a DL/LL ratio of 3.0 for bridge structures and Paikowsky et al., 
(2004), suggested that the ratio should be within the range of 2.0 to 2.5, since it is 
reasonable and applicable for long span bridges. According to Allen (2005) and 
Paikowsky et al. (2004), the DL/LL ratio has a small infiuence on the LRFD resistance 
factors when calibrated based on the reliability theory. Allen (2005) considered a DL/LL 



68 



ratio of 3.0 to be consistent with the previous work done by Barker (1991), and thus it 
can directly compare with the developed resistance factors 

Table 4.1 Resistance Factors Calibrated by Fitting with ASD 
for Yd = 1.25 and Yl = 1.75 (After McVay et al, 1998). 



QD/QL 


Resistance Factor, FS 






rb— Z.U 


rb— Z.J 


r 5>— j.U 


rJ>— J.J 


rb— 4.U 


1 


1.00 


0.75 


0.60 


0.50 


0.43 


0.38 


2 


0.94 


0.71 


0.57 


0.47 


0.40 


0.35 


3 


0.92 


0.69 


0.55 


0.46 


0.39 


0.34 


4 


0.90 


0.68 


0.54 


0.45 


0.39 


0.34 


5 


0.89 


0.67 


0.53 


0.44 


0.38 


0.33 


6 


0.88 


0.66 


0.53 


0.44 


0.38 


0.33 


7 


0.88 


0.66 


0.53 


0.44 


0.38 


0.33 


8 


0.87 


0.65 


0.52 


0.44 


0.37 


0.33 


9 


0.87 


0.65 


0.52 


0.43 


0.37 


0.33 


Median 


0.94 


0.70 


0.56 


0.47 


0.39 


0.34 


Recommended 


0.90 


0.65 


0.55 


0.45 


0.35 


0.30 



4.2 Calibration by Using Reliability Theory 

The objective of the reliability theory is to limit the probability of failure (Pf), probability 
of loads exceeding the resistances, of structures to a certain acceptable extent. As shown 
in Figure 4.1, Q and R are two PDFs representing the loads and resistances, respectively 
and the area of overlap between the two PDFs is considered as failure. By subtracting the 
two PDFs (R - Q), the area to the left of the zero axis is considered to be the failure 
region and the probability of failure can be determine by using the reliability index (P). 
The reliability index stands for the number of standard deviations (a) representing the 
distance between the zero axis and the mean of R - Q. The general process used by 
Barker, et al. (1991) and Paikowsky, et al. (2004) to develop the regionally calibrated 
LRFD resistance factors based on the reliability theory is as follows: 
• Collect data required for statistical analysis 



68 



• Calculate statistical parameters for load and resistance PDFs: the Mean, 
Standard Deviation, and Coefficient of Variation (COV) 

• Determine the best-fit distribution for each PDF 

• Choose the appropriate statistical method for calibration (FOSM, FORM, 
Monte Carlo Simulation Method) 

• Use the recommended load factors provided in the design code 

• Select a reliability index P based on the margin of safety required in design 
specifications, and by considering the recommended levels of reliability used 
for geotechnical designs 

• Calculate resistance factors for design 

4.2.1 Load, Resistance Bias Factor 

The load, resistance bias factor is defined as: 



X ^'"^ (-4 4) 



where: Rm= measured resistance, Qm= measured load 
Rn = predicted resistance, Qn = predicted load 
The mean, standard deviation and coefficient of variation of the set of bias data 

^Ri(orQi) ^^Q'- 

Mean: ^^^^^^^^ = (4.5) 

Standard deviation: ^R(orQ) - '^ '^'^ ■ 

Coefficient of variation: COF^^^^g, = ^^^^ (4.7) 

The bias factors and coefficients of variation for load components can be developed 
in a fairly straightforward manner. Physical measurements can be made of various 




69 



weights of materials and their statistics calculated. Vehicle live loads and their 
variations can be measured without interference to vehicles using weigh-in-motion 
instrumentation. From this load data, the load statistics can be compiled and 
tabulated. 

The results of statistical analysis of highway dead and live loads are summarized in 
Table 4.2 (Nowak, 1993). The largest variation is the weight of the wearing surface 
placed on bridge decks. Also of interest, as indicated by the bias factor, is that the 
observed actual loads are greater than the specified nominal values. 



Table 4.2 Xqd, A,ql, COVqd, COVql as recommended by AASHTO 



(cited in Withiam etal, 1997) 



Load component 


X 


cov 


Dead load (qd) 


Factory-made 


1.03 


0.08 


Cast in Place (CIP) 


1.05 


0.10 


Asphalt wearing surface 


1.00 


0.25 


Live load (ql) 


1.15 


0.18 



4.2.2 Probability Density Function 



Based on the distribution of the resistance data, a lognormal probability distribution 
was recommended for the resistance data by the AASHTO Specification. Equation 
(4.8) presents the lognormal probability density equation using to calibrate the 
resistance factor for depth foundation in design. 



1 



exp 



1 




2 


2 


^ ^ J 





(4.8) 



In Equation (4.8) the values of A. and C, are the lognormal mean and lognormal 
standard deviation respectively. 



70 



f 



^'=ln 1 + 



cr 



(4.9a) 



A = In ju — 
2 




(4.9b) 



Where: a and [x, are the standard deviation and the mean of the resistance or load as 
defined in prior sections. 

4.2.3 The First Order Second Moment (FOSM) Method 

In design practice, there are usually two types of limit states: ultimate limit states and 
serviceability limit state. Each can be represented by a performance function of the 
form, g(X) = g(Xi, Xj, Xn) in which X is a vector of basic random variables (Xi, 
X2, Xn) for strengths and loads. The performance function g(X) is sometimes 
called the limit state function. It relates the random variables for the limit-state of 
interest. The limit state is defined when g(X) = 0, and therefore, the failure occurs 
when g(X) < 0. This method uses the first terms of a Taylor series expansion of the 
performance flinction to estimate the expected value and variance of the performance 
fiinction. 



By assuming all the {x. - ju^ ) terms are small, their squares and cubes and higher 
powers will be smaller and can be ignored. Then, the first order terms give: 



g(Xi , Xi x„ ) ~ g(//^i , //^i ,....,//;,„) + - ^ (x, ) 



dg 




(4.10a) 




1' 



dg_ 
dx. 



(4.10b) 



71 



Since only first order term is included, methods based on this assumption are called 
first order method. To find the expected value of g, it needs to integrate g multiplied by 
the joint probability density fiinction of the variables Xi through Xn from - oo to + oo . 



Mg=f gixi,x„....,xjf^.{x_)dx.^j^ I g{ju^„jU^^,....,jU^J + Y,ix^-Mxi) fx,(x,)dx. (4.11) 

p +00 /• +00 ^L, 

Since , //^j //^J is constant, f^. (x. )dx. = 1 and > (x. -Mxi)fxi )^-^, = 

J -00 J —00 

i=\ 

The expected value of g can be expressed by following equation: 

M,~g{f^xx^f^xi^-;f^xn) (4-12) 



The variance of function g is: 

Var[g] = cT;-=E[{g-^^f] 

And from equation (4.10b) and (4.13) 



( n 



dx, 



(4.13) 



(4.14) 



V '=1 ^-^i J 

Multiplying the expression in brackets by probability density function and integrating 
over the complete range of probabilities leads to an expression for the variance: 

dg dg 



5x. dx. 



og 
kSx^j 



i=\ j*i 



dg dg 
dx. dxj 



(4.15) 



(4.16) 



Since the variance in form of the second moment and is the highest order statistical 
result used in analysis, it is also called a second moment method. 
If g is a linear function of the variable xi: 



g(Xi , Xi x„ ) = ajXi + a2^2 + + ««^« = X ^'^i 



(4.17) 



72 



Mean and variance of function g could be expressed by following equation 

n 

Mg = a,Mx, + «2/"x, + + (^nMx„ = Z ^-v"^, (4.18) 

1=1 

ti n 

= Z Z '^fljPx.^Xj ^x, ^x, (4- 1 9) 

,=1 j=\ 

4.2.3.1 Reliability indexp 

If the performance function g has two variables which are load Q and resistant R: 

g = R-Q (4.20) 

from the equation (4.18) and (4.19), the mean and variance of g is 

^g=^R-^Q (4-21) 
o-/ = C7^' + cJq - Ip^qCj^cJq (4.22) 

The reliability index, |3, is defined as: 

p = ^= ^ (4.23) 
If the load and resistance are uncorrected, the correlation coefficient is zero and 



In this study, the load (Q) and the resistance (R), are assumed to be lognormally 
distributed. The limit state fiinction in this case is defined as: 

g (R, Q) = In (R) - In (Q) = In (R/Q) (4.25) 



73 




^ RELIABIUTf " 




FAILURE REGION 
AREA = P) 



5 . en(R/Q) 



g - (r(R/a) 



BOUNDARY 

Figure 4.1 Distribution of load and resistance and reliability index, P 

Since R and Q are lognormally distributed, ln(R) and ln(Q) are normal distribution. 
Thus, the mean value of g (R, Q) can be expressed as: 



Where: 



g = ln(i?)-ln(0 



1 



(4.26) 



ln(i?) = \niR) - -ln(l + COV\) = \n(R) - ln(l + COV\y 
R 



hi(i?) = hi 



(4.27) 



2 nO.5 



HQ) = HQ)-^W + COV\) = ln(0-ln(l + COr^g) 

Q 



ln(0 = ln- 



From equation (4.26), (4.27) and (4.28) 



(4.28) 



R 



g = ln 



R 



In- 



Q 



^\+cov\ ^\+cov 



:lni±^ = ln 

Q 



Q^\+cov\ 



or g = In 



R \\ + COV\ 



And its standard deviation is: 



(4.29) 



74 



?.=yl^'HF,+^'m^ (4-30) 

where: 

^'M^=ln(l + COF^,) (4.31a) 

a'^^=H\ + COV\) (4.31b) 
From equation (4.30), (4.31a) and (4.31b) 

=^ln(l + COF^,) + ln(l + COF^g) 

or 



g^=^Hl + COV\)il + COV'Q) (4.32) 

where : 

R and Q : mean values of resistance and load 
COVr, COVq : coefficient of variation of R and Q 

The reliability index P is defined as the ratio between the lognormal mean, g , and the 



lognormal standard deviation, ^, of the ln(R/Q) series: 



{R I Q)p + COV\)l{\ + COV\) 



(4.33) 



4 ^H\ + COV\){\ + COV\) 

The mean values of the load resistance can be expresses in terms of nominal 

load and resistance and their respective bias factors such that: Q = XqQ„ andi? = 

The equation (4.33) can be written as: 

In [(A,R„ I XqQ„ ) ^{\ + COV\)l{\ + COV\) 



P + COV\)l{\ + COV\) 
Rn and Qn can be expressed in terms of factor of safety (FS) such that 
Rn=FSxQn Consider the load combination of dead load (Qd) and live load (Ql) for 
AASHTO Strength Case I. Then, IqQvl = }iqdQd + ^qlQl and Rn = FS (Qd + Ql). 



(4.34) 



75 



2 2 

Also, Qd and Ql are assumed to be mutually independent and COVq = COVqd + 
COVql Therefore, Equation (4.34) can be rewritten in the following format: 



In 

P = - 



Yn^"^ p ^ cOV\, + COr-^,)l{\ + COV\) 



^hi(l + COV\){\ + COV\^ + COV\, ) 
Or can be written as 



(4.36) 



In 

y9 = - 



^qdQd I Ql + '^QL 



^(1 + cov\, + cov\j(\ + cov\ ) 



(4.37) 

/ln(l + COV\ )(1 + COV'q^ + COV\, ) 

It is seen from this equation that the reliability index is a function of FS, Qd/Ql, 
the load statistics (A,qd, ^ql, COVqd, COVql) and the resistance statistics (^r, COVr). 
Hansell and Viest, 1971 developed the following empirical equation for the Qd/Ql 
ratio: Qd/Ql = (1+ IM) * 0.0132 L (4.38) 

Where: IM = Dynamic load allowance factor (usually equal to 0.33) 
L = Span length (feet) 

Qd/Ql usually ranges from 1.0 to 3.0 (corresponding to L = 57-170 ft). 
In LRFD specifications, the targeted reliability index (P) is defined as the measure 
of safety associated with a probability of failure (Pf). The probability of failure 
represents the probability of the condition, at which the resistance multiplied by the 
resistance factors will be less than the load multiplied by the load factors. A very 
precise definition of probability of failure, pf, is in terms of reliability index, Fu(P) 
(Withiamet al. 1997). 

P^^X-FXP-) (4.39) 



76 



O 




-1 1 
Reliablity Index, P 

Figure 4.2 Reliability definition based on standard normal probability density function 
Fu(x) is the standard normal cumulative distribution function. 



CO -| 



exp 



1 



(4.40) 



The shaded area in Figure (4.2) represents the probability of failure, pf, to 

achieve a target reliability index, Pt. 

Table 4.3 Relationship between Probability of Failure and Reliability Index 
for Lognormal Distribution (After Withiam et al., 1997). 



Reliability 
Index P 


Probability of 
Failure pf 


2.5 


0.99x10"' 


3.0 


1.15x10"^ 


3.5 


1.34x10"^ 


4.0 


1.56x10"^ 


4.5 


1.82x10"^ 


5.0 


2.12x10"^ 


5.5 


2.46x10"^ 



Probability of 
Failure pf 


Reliability 
Index (B 


10-^ 


1.96 


1.10"^ 


2.50 


1.10"^ 


3.03 


1.10-' 


3.57 


1.10"^ 


4.10 


1.10"^ 


4.64 


1.10"^ 


5.17 



Another commonly accepted relationship between the reliability index, P, and 
the probability of failure, pf, has been developed by Rosenblueth and Esteva (1972) 
using the relationship for values between 2 and 6. 



77 



pf=460 e(-4.3p) 



(2<p<6) 



(4.41) 



« 

SI 


2 

3 



1.0E+00 
1.0E-01 
1.0E-02 
1.0E-03 
1.0E-04 
1.0E-05 
1.0E-06 
1.0E-07 
1.0E-08 
1.0E-09 
1.0E-10 









^ Pf = 


1 

460 exp (-4.3 b) 












EstE 


'va et al. (19' 


'2) 






















True value 
Withiam et al 














(1997) 

















































































Reliability index,P 

Figure 4.3 Comparison of Esteva and Withiam methods to obtain reliabihty index, P 

For civil engineering project, P usually ranges from 2.0 to 4.0. However, due to the 
redundancy of pile groups, AASHTO and FHWA recommend using P from 2.0 to 3.0 
for pile foundations (cited in Withiam et al., 1997), and it is called the target 
reliability index Pt. 

4.2.3.2 Recommended Target Reliability Index 

For depth foundation design, the target reliability index, Pt, could range from 2.5 to 
3.0, which is corresponding to the range of approximate failure possibility of 1% to 
0.1%, according to Barker et al. (1991a). However, Paikowsky, et al. (2004) indicated 
the more accurate failure probability for target reliability index of 2.5 and 3.0 is 
0.62% and 0.14%), respectively. Additionally, for axially loaded pile, Paikowsky, et 
al. (2004) recommended a Pt of 2.33, which is corresponding to failure probability of 
1%, for redundant piles, defined as 5 or more piles per pile cap, and a pT of 3.0 for 
non-redundant piles, defined as 4 or less piles per pile cap. 



78 



P = 3.00 Pf=0.1% 



P = 2.33 
Pt= 1.0% 



• SSI ^ 

Non - ReduiKlant 



Logically Redundant 
Hon- Redundant 



Figure 4.4 Redundant vs. non-redundant pile support, Paikowsky, et al. (2004) 
4.2.3.3. Efficiency of Different Methods 

McVay (2000) suggested an efficiency factor to determine the efficiency of different 
static methods that are relative to the actual pile behavior and to each other. This 
efficiency factor (cp/A,) is equal to the ratio of the resistance factor to the mean bias of 
the method. The cp/A factor ranges from to 1 .0, in which a higher (p/X is proportional 
to a higher efficiency. The efficiency factor reflects the economy of the design. The 
efficiency of a static method is not dependent on the corresponding LRFD resistance 
factor. For example, the factored pile design capacity, calculated using a specific 
static method, can be lower than that calculated using another static method, although 
the resistance factor of the first method may be higher than the second. This is 
essential because the first method might be underestimating the nominal pile capacity, 
while the second method could be overestimating it. By multiplying both methods 
with the corresponding LRFD resistance factors, the method with the lower resistance 
factor could yield a higher pile capacity overall. 

4.2.3.4 Equivalent Factor of Safety 

The economy of the LRFD resistance factors can also be measured by means of the 
equivalent factor of safety (FS) corresponding to the ASD. This equivalent FS is 
calculated based on the simplified relation provided in equation in Chapter 2. The 
equivalent FS is presented for each group based on a DL/LL = 2, yL = 1 .75, and yD = 



79 



1 .25, the FS=1 .4167/q). On the other hand, the actual FS is calculated by multiplying 
the mean bias by the equivalent FS. The actual FS represents the overall economy of 
the method, meaning that whenever the actual FS is lower, the foundation cost is 
reduced and vice versa. 

4.2.3.5 Resistance Factor Calibration 

The basic equation for LRFD was expressed as equation (2.2) and is rewritten here in 
the following format: 

(t> = ^^ (4.42) 

The nominal resistance R can be replace by the mean value {R) and the resistance 
bias factor ( /l^ ) then, 

R 

From equation (4.33) i? can be replaced by the following equation: 



- Q exp(A^ln [(l + COF/ ) (l + COVq ) 
^[\ + COVq')i(\ + COV,') 
The equation (4.44) can be rewritten in the following form: 



(4.44) 



^_ K[Y.ra)ii^c ov,^)i[i^cov,') ^^^^^ 

e exp(^^ln [(l + COF/ ) (l + COVq' )] 

The mean values of the load resistance can be expressed in terms of nominal load and 
resistance and their respective bias factors such that: Q = ?^qQ„ and R = 



<p = , (4.46) 

(^a a + ^& Qo ) exp(;5^hi [(l + cor/ ) (l + COF/ 



80 



Diving the 



^ Q ^ 



[\ + COVq; + COVq^')i[\ + COV,') 



' Qo ' (4.47) 

A.„ 1- A.^ 

tii J 



exp(y9 Jin [(1 + COF/ ) (l + COFg/ + COF^; y 



As recommend in AASHTO, the following parameters: dead load factor- Yd = 1.25, 
live load factor- yl = 1.75, dead load bias factor-XQD= 1.08, live load bias factor-XgL 
= 1.15, dead load coefficients of variation-COVgD = 0.13 and live load coefficients of 
variation COVql= 0.18 could be used in equation 4.46 to calibrate the resistance factor 
4). Sine dead to live load ratio Qd/Ql changes from 1-3 and has almost no effect on the 
resistance factor, this study uses Qd/Ql = 1- 

4.2.4 First-Order Reliability Method (FORM) Analysis 

The basic concepts and analytical procedures of the The First Order Reliability 
Method (FORM) methods were developed by Ditlevsen (1974), EUingwood, et al. 
(1980), Hasofer and Lind (1974). The first step in the Hasofer-Lind approach is to 
reformulate the problem with dimensionless variables. If the performance function g 
has n uncertain variables (Xi, X2,. . .Xn) and each variable Xi is defined in terms of its 
[jLxi and its standard deviation axi, a primed variable, which is dimensionless and has 
the mean value of zero and unit standard deviation of primed variables could be 
defined by the following equation: 

x\= ' (4.48) 



81 



9W 




'^^-'1' Variable a:. 

Figure 4.5 Limit state function and pdf of basic random variables 
(Baecher and Christian 2003) 




Figure 4.6 Transformed basic variable spaces. (Baecher and Christian 2003) 

From the above definition, the basic case of reUabihty of a system with loading Q (or 
Xi) and resistance R (or X2) can be expressed in form of prime variables 



82 



R' = ^-^ (4.49) 



R 



The performance function g for the margin of safety becomes: 

g = i?-g = a,i?'-aee'+//,-//g (4.51) 

The origin point at which both R and Q equal their values and the distance d between 
the origin and the line g = is: 

d= (4.52) 

The distance d is identical to the definition of the reliability index (B. This result 
suggests that the reliability index can be interpreted geometrically as the distance 
between the point defined by expected values of the variables and the closest point on 
the failure criterion. 

The following step-by-step procedure, proposed by Ang and Tang 1984, could be used 
to find the reliability index (3 (dmin)- 



Step 1: 

Assume an initial value for the design point. It is common to start with the 
mean values of the basic random variables. The design point in the reduced 
coordinates should then be computed as 

X * — Li 

x.*'= ' (4.53) 

Where: jUj^ = mean value of the basic random variable Xi, a^^ = standard 

deviation of the basic random variable Xi. The notations x* and x'* are used to 
denote the design point in the regular coordinates and in the reduced coordinate 
system, respectively. 



83 



Step 2: 

If the distribution of basic random variables is non-normal, approximate this 
distribution with an equivalent normal distribution at the design point, having 
the same tail area and ordinate of the density fianction with equivalent mean, 

^.'^ ^x^-f\F,ix^))cT,' (4.54) 
and equivalent standard deviation 

fxM) 

Where: 

fj.^'^ = mean value of the equivalent normal distribution 

cr^ ^ = standard deviation of the equivalent normal distribution 

F{x*) = original cumulative distribution function (CDF) of Xi evaluated at 

the design point 

f{x*) = original PDF of Xi evaluated at the design point 
(!)(•) = CDF of the standard normal distribution 
(j) (•) = PDF of the standard normal distribution. 

Step 3: 

Set x'* = -a. * P ,m which the a. * are direction cosines. Compute the 
directional cosines {a.* ,\ = 1,2, , n) using 



dg 
dx' 



,=1 V 



dg 



dx' 



(4.56) 



84 



Where 



dg 



XCTv 



step 4: 



With //^/^ > cr^ ' "^^^ known, the following equation is solved for P: 



(4.57) 



Step 5: 



Use the P obtained from step 4, a new design point is obtained from 



(4.58) 



Step 6: 



Repeat steps 1 to 6 until convergence of P is achieved. 



In this study, the limit state function, g, could be expressed by following equation: 

^ (4.59) 



g = ln(i?)-ln(Xa) = ln 



la 



If we only consider the dead loads and live loads, the limit state function can 
be rewritten in terms of bias factors of the load and resistance as follows: 



g = ln- 



(4.60) 



(l>R = yQoQD+yQLQL (4.6i) 

Substituting R from Equation (4.36) to Equation (4.35) yields the following 
limit state flinction in terms of the random variables /i.^,/lg£i and 



g = ln 



(4.62) 



4.2.5 Monte Carlo Simulation Method 



85 



For more complicated limit state functions, the application of the general 
statistical method for the calculation of the reliability index is either extremely 
difficult or impossible. Under this circumstance, the Monte Carlo simulation provides 
the only feasible way to determine the reliability index or the probability of failure. 



The Monte Carlo method is a technique by which a random number generator is 
used to extrapolate CDF values for each random variable. Extrapolation of CDF 
makes estimating P possible; otherwise, a limited quantity of data would restrict the 
reliable estimate of (3. Once the reliability index,p, is estimated, the probability of 
failure can be estimated by assuming the distribution of g(x). The steps of the Monte 
Carlo simulation method are as follows: 



Stepl: Generate random numbers for each set of variables. 

Here there are three variables (resistance, dead load and live load bias factor), so three 
sets of random variable have to be generated independently for each one. The number 
of simulations required is found using the following equation: 

7V = i^^ (4.63) 
V (P ) 

p y true J 

Where, Ptrue is the lowest magnitude of probability that is to be determined using 
Monte Carlo, and Vp is the desired coefficient of variation of the simulation result. 
To estimate a probability as low as 10-2 and keep variance under 10 percent, the 
number of points to be generated in the Monte-Carlo simulation is 9900. 

For each normal variable, the sample value xp is estimated as: 

Xi(random) ~ |J-x (1+ ZiCOVx) (4.64) 
For each lognormal variable, the sample value Xi{random) IS estimated as: 



86 



Xi(random) = exp()iinx+Ziainx) (4.65) 

Where: 

ata = ln(COVx'+l)°' Htax= ln(|ix)-0.5a'tax (4.66) 

|j,x: the mean of x 

COVxi the covariance of x 

|j,inx : the equivalent lognormal mean of x 

oinx'. the equivalent lognormal standard deviation of x 

Zi =NORMSrNV(RAND())i is the random standard normal variable generated using 
the Matlab function. 

In the Monte Carlo simulation, the program generated N groups of random numbers. 
Each group consisted of 3 random numbers zi, Z2, and Z3 are normally distributed 
from to 1 . The dead load (DL) and live load (LL) bias factor is normal distribution 
and resistant bias factor is lognormal distribution. The program then calculated 
random live load LLrandom, dead load DLrandom, and resistance Rrandom using the 
following equations: 

i^i^random=LL.kL.(l+Zl.COVLL) (4.67) 

£'i^random=DL.:^DL.(l+Z2.COVDL) (4.68) 

^radom = exp(mnR+Z3ai„R) (4.69) 

where: 

ai„R = Ln(COVR'+l)''-' (4.70) 

M.. = Ln(/.,. ^^-^^^^^^-^^M -0.5a^^ (4.71) 
Step 2: Define the limit state function. 

From each group of random loads and resistance, the safety margin was calculated 
using equation 



87 



^ — Rrandom LL random — DLrandom (4.72^ 

Step 3: Find the number of cases where g < 0. 

hi this equation (j) is a trial resistance factor. LL and DL are the nominal live load and 
dead load. Yll , Ydl , ^ll , ^dl , COVll and COVdl are listed in the Table . The 
values for |a,R and COVr are calculated from the measure capacity and nominal 
capacity. Paikowsky et al. (2004) found out that the calibrated resistance factor is not 
sensitive to the change of DL/LL. So in this study the DL/ LL ratio of 2.0 was 
selected. The only unknown variable is the nominal live load LL. In the Monte Carlo 
simulation, the magnitude of the nominal load would not affect the result so that LL 
was simply set to one. 



The probability of failure is then defined as: 

countig<0) 

^ N 

and reliability index P is estimated as: 

p=0"'(Pf) (4.74) 

If the calculated reliability index (P) is different from the selected target reliability 
index (Pt), the trial resistance factor (P) in step 1 should be changed and iteration 
needs to be done until |P-Pt| < tolerance. Prior to the Monte Carlo simulation, a target 
reliability index Pt and a ratio of dead load must be selected. To be consistent with 
the AASHTO LRFD Specifications, Pt = 3.0 for a common design and Pt = 2.33 for a 
shaft group with five or more drilled shafts were considered. 



88 



5. Resistance Factor Calibration for the Data from Difference Locations in 
NCHRP Report 507 

5.1 Introduction 

When design depth foundation in specific location, If we use the resistance factor 
from report 507, it's may be too low since the author of report 507 use all the data from 
different locations to calibrate the resistance factors for depth foundation. The purpose 
of this chapter is to investigate the geo-materials dependence of resistance factor from 
difference locations by separating the data from NCHRP report 507 and calibrating the 
resistance factor for different locations. 

In the NCHRP report 507, Paikowsky collected numerous static load and dynamic 
load tests for driven piles from different states in US and different locations in the 
world. 368 dynamic measurements with signal matching analysis (CAPWAP) cases 
including 240 cases of end of driving (EOD) and 128 cases of beginning of retrike 
(BOR) were found in report 507 to be usable in this study. 

Beside PDA data, 131 concrete piles have soil profile and static load test including 
19 cases in cohesive soil, 37 cases in cohesionless soil and 85 cases in mixed soil are 
also useful for calibration resistance factor for concrete piles using static methods 

Two methods, including First Order Second Moment Method (FOSM) and First- 
Order Reliability Method (FORM), are using to calibrate the resistance factor for driven 
piles. In data base some places have small data, 1 to 6 pile cases, in order to have 
enough data to calibrate resistance factor this study only consider for the locations have 
more than 7 pile cases 

5.2 Calibration Resistant Factor for Driven Piles Using CAPWAP Method 

5.2.1 Resistance Factor for Different Locations by Using CAPWAP (BOR+EOD) Data 

Table 5.1a and 5.1b show the resistance factor calibration by using both FOSM and 
FORM with reliability index p=2.33 and p=3.0 for driven piles using CAPWAP 
method with both BOR and EOD data. The detail calibration resistance factor cj) by 



89 



using FORM is in the appendix A (from Fig A- la to Fig A- 13b) and by using FOSM 
method is in the appendix C (from table C-1 to table C-13). Figure 5.1 and 5.2 show the 
different resistance factor cj) for different location with reliability index P=2.33 and 
P=3.0. The resistance factor cj) varies with different locations. S Carolina has the lowest 
resistance factor whereas Oakland, CA has the highest resistance factor 



Table 5.1a Resistance Factors for Driven Piles using 
CAPWAP (BOR+EOD) for Different Locations 



Location 


Total 


Florida 


Winconsin 


Lousiana 


Massachusetts 


S Carolina 


Number of Cases-N 

Mean-\ 
Standard deviation-a 
COV 


368 


107 


27 


22 


17 


16 


1.426 


1.324 


1.353 


2.743 


1.515 


1.411 


0.912 


0.571 


0.742 


2.502 


0.758 


0.930 


0.639 


0.431 


0.548 


0.912 


0.500 


0.659 


$ (FOSM) 


p=2.33 


0.386 


0.564 


0.446 


0.425 


0.555 


0.306 


p=3.0 


0.254 


0.412 


0.307 


0.247 


0.392 


0.199 


$ (FORM) 


p=2.33 


0.406 


0.611 


0.478 


0.443 


0.595 


0.388 


p=3.0 


0.277 


0.467 


0.340 


0.266 


0.433 


0.261 



Table 5.1b Resistance Factors for Driven Piles using 
CAPWAP (BOR+EOD) for Different Locations 



Location 


Ortanrio 


Alabama 


Pennsyvania 


Oakland, CA 


Nebraska 


Canada 


Oklahoma 


Number of Cases-N 

Mean-X 
Standard deviation-a 
COV 


15 


14 


12 


13 


9 


8 


7 


1.160 


1.397 


0.881 


1.843 


1.237 


0.967 


1.529 


0.294 


0.383 


0.201 


0.671 


0.423 


0.209 


0.635 


0.254 


0.274 


0.228 


0.364 


0.342 


0.216 


0.415 


$ (FOSM) 


p=2.33 


0.715 


0.828 


0.570 


0.908 


0.638 


0.640 


0.675 


p=3.0 


0.573 


0.656 


0.462 


0.688 


0.489 


0.521 


0.498 


$ (FORM) 


p=2.33 


0.809 


0.931 


0.652 


0.996 


0.704 


0.736 


0.733 


p=3.0 


0.779 


0.675 


0.767 


0.779 


0.558 


0.626 


0.558 



90 










0) 




m 




« 




o 




CO 








BUJOL|B|>jO 



BpBUBO 



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BjUBAASUUSd 



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OUUBIJO 



VO PUE|>|BO 



BU!|OJBO s 



SU8SnL|0BSSB|/\| 



BUBISnO") 



ujSuooujM 



Bpuoy 



IBIOI 



o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 


o 




o 


O) 


00 


1^ 


CD 


in 




CO 






o 






o 


o 


o 


o 


o 


o 


o 


o 


o 


o 



<^ jojOBi aouEjsissy 



91 




ELUOU|E|>jO 



B>)SBjq8N 



BjUBAAsuued 



ELueqEiv 



OUUBUO 



VO 'PUB|>)B0 



BU!|OJBO S 



suasnnoBSSE|/\| 



BUBisno"! 



ujSuooujM 



Bpuoy 



IBIOI 



p 
II 

02. 



O 
PQ 
+ 
Q 
O 
W 

< 

< 
U 



> 
Q 



O 

[In 
O 

c 



Pi 

<N 
IT) 



o 





























o 





























02 


00 


r-. 


CO 






CO 


C\l 


































d 



92 



5.2.2 Resistance Factor for Different Locations by Using CAPWAP (BOR) Data 

Table 5.2 shows the resistance factor calibration by using both FOSM and FORM with 
reliability index (3=2.33 and (3=3.0 for driven piles using CAPWAP with BOR data. The 
detail calibration resistance factor 4> by using FORM is in the appendix A (from Fig A- 14a 
to Fig A-20b) and by using FOSM method is in the appendix C (from table C-14 to table C- 
19). Figure 5.3 and 5.4 show the different resistance factor cj) for different locations with 
reliability index (3=2.33 and (3=3.0. The resistance factor cj) varies with different locations. 
Wisconsin has the lowest resistance factor whereas Louisiana and Ontario have the highest 
resistance factor. 



Table 5.2 Resistance Factors for Driven Piles using CAPWAP (BOR) for 

Different Locations 



Location 


Total 


Florida 


Wisconsin 


Louisiana 


Caronila 


Alabama 


Ontario 


Number of Cases-N 

Mean-\ 
Standard deviation-a 
COV 


240 


85 


18 


15 


13 


9 


8 


1.220 


1.243 


0.964 


1.698 


1.158 


1.230 


1.118 


0.454 


0.475 


0.286 


0.592 


0.285 


0.351 


0.180 


0.372 


0.382 


0.296 


0.349 


0.246 


0.285 


0.161 


$ (FOSM) 


p=2.33 


0.590 


0.589 


0.547 


0.863 


0.703 


0.713 


0.809 


p=3.0 


0.445 


0.442 


0.429 


0.659 


0.565 


0.562 


0.675 


$ (FORM) 


(3=2.33 


0.652 


0.645 


0.610 


0.950 


0.824 


0.802 


0.953 


p=3.0 


0.505 


0.498 


0.497 


0.750 


0.688 


0.655 


0.836 



93 




Total Florida Wisconsin Louisiana Caronila Alabama Ontario 

Figure 5.3 Resistance Factors ^ for Driven Piles Using CAPWAP (BOR) with p =2.33 



0.900 
0.800 
0.700 

-e- 

o 0.600 
o 

CO 

u. 

<u 0.500 
o 

CO 

M 0.400 

03 
CD 
CC 

0.300 
0.200 
0.100 
0.000 



□ FOSM 
■ FORM 



240 cases 85 cases 1 8 cases 



15 cases 



i 



1 3 cases 



9 cases 



8 cases 

I 



Total 



Florida Wisconsin 



Louisiana 



Caronila Alabama 



Ontario 



Figure 5.4 Resistance Factors cj) for Driven Piles Using CAPWAP (BOR) with P =3.0 



94 



5.2.3 Resistance Factor for Different Locations by Using CAPWAP (EOD) Data 

Table 5.3 shows the resistance factor calibration by using both FOSM and FORM with 
reliability index (B=2.33 and |3=3.0 for driven piles using CAPWAP with EOD data. The 
detail calibration resistance factor cj) by using FORM is in the appendix A (from Fig A-21a 
to Fig A-27b) and by using FOSM method is in the appendix C (from table C-20 to table C- 
25). Figure 5.5 and 5.6 show the different resistance factor cj) for different location with 
reliability index (3=2.33 and (3=3.0. The resistance factor cj) varies with locations. Pittsburgh, 
PA has the lowest resistance factor whereas Oakland, CA and Wisconsin have the highest 
resistance factor. If including all the EOD data from different location, the resistance factor 
will be the lowest one 



Table 5.3 Resistance Factors for Driven Piles (EOD) using CAPWAP for 

Different Locations 



Location 


Total 


Florida 


Massachusetts 


Pittsburgh, PA 


Oakland, CA 


Wisconsin 


Ontario 


Number of Cases-N 

Mean-\ 
Standard deviation-a 

cov 


128 


18 


11 


9 


8 


8 


7 


1.789 


1.503 


1.728 


0.820 


2.191 


2.294 


1.208 


1.337 


0.650 


0.904 


0.192 


0.629 


0.637 


0.399 


0.748 


0.433 


0.523 


0.235 


0.287 


0.278 


0.330 


$ (FOSM) 


p=2.33 


0.385 


0.638 


0.602 


0.524 


1.265 


1.349 


0.639 


p=3.0 


0.241 


0.467 


0.419 


0.423 


0.997 


1.068 


0.493 


$ (FORM) 


p=2.33 


0.456 


0.654 


0.644 


0.596 


1.416 


1.515 


0.706 


p=3.0 


0.265 


0.498 


0.462 


0.503 


1.154 


1.243 


0.565 



95 




Fii 



Total Florida Wisconsin Louisiana Caronila Alabama Ontario 

;ure 5.5 Resistance Factors cj) for Driven Piles Using CAPWAP (EOD) with (3 =2.33 



0.900 -I 



o 
CO 



a> 
o 
c 

B 

0) 

DC 




Total Florida Wisconsin Louisiana Caronila Alabama Ontario 

Figure 5.6 Resistance Factors cj) for Driven Piles Using CAPWAP (EOD) with |3 =3.0 



96 



5.3 Calibration Resistant Factor for Driven Piles Using Static Analysis 

5.3.1 Resistance Factor for Concrete Piles in Cohesionless from Different Locations 

The resistance factor calibration from all 37 data for concrete in cohesionless soil by 
using different static method, Nordlund, beta, Meyerhof, Schmertmann SPT are showed in 
table 5.4a and for the Florida data only is showed in table 5.4b. 



Table 5.4a Resistance Factors for Concrete Piles in Cohesionless Soil 



Method 


Nordlund 


3 


Meyerhof 


Schmertmann SPT 


Number of Cases-N 

Mean-X 
Standard deviation-a 

cov 


37 


37 


37 


37 


1.06 


1.17 


0.64 


1.25 


0.55 


0.56 


0.42 


0.62 


0.52 


0.48 


0.65 


0.49 


$ (FOSM) 


p=2.33 


0.37 


0.45 


0.17 


0.46 


p=3.0 


0.26 


0.32 


0.11 


0.33 


$ (FORM) 


3=2.33 


0.4 


0.483 


0.183 


0.5 


3=3.0 


0.289 


0.356 


0.125 


0.364 



Table 5.4b Resistance Factors for Concrete Piles in Cohesionless Soil for 

Florida Data Only 



Method 


Nordlund 


3 


Meyerhof 


S chmertmannSPT 


Number of Cases-N 

Mean-\ 
Standard deviation-a 
COV 


27 


27 


27 


27 


1.113 


1.216 


0.591 


1.191 


0.525 


0.545 


0.358 


0.508 


0.471 


0.448 


0.606 


0.427 


$ (FOSM) 


3=2.33 


0.43 


0.50 


0.17 


0.51 


3=3.0 


0.31 


0.36 


0.12 


0.38 


(FORM) 


3=2.33 


0.469 


0.54 


0.183 


0.557 


3=3.0 


0.347 


0.403 


0.125 


0.42 



97 



5.3.2 Resistance Factor for Concrete Piles in Cohesive for Different Locations 

The resistance factor calibration from all 19 data for concrete in cohesive soil by using 
different static method, a-API revised, a-Tomlinson, \ are showed in table 5.5a and for the 
Louisiana data only is showed in table 5.5b. 



Table 5.5a Resistance Factors for Concrete Piles in Cohesive Soil 



Method 


a-API revised 


a-Tomlinson 


X 


Number of Cases-N 

Mean-\ 
Standard deviation-a 
COV 


19 


19 


19 


0.89 


0.94 


0.79 


0.31 


0.50 


0.25 


0.35 


0.54 


0.32 


$ (FOSM) 




0.45 


0.32 


0.30 


p=3.0 


0.34 


0.22 


0.21 


$ (FORM) 


p=2.33 


0.498 


0.34 


0.342 


p=3.0 


0.393 


0.243 


0.243 



Table 5.5b Resistance Factors for Concrete Piles in Cohesive Soil for 
Louisiana Data Only 



Method 


a-API revised 


a-Tomlinson 


\ 


Number of Cases-N 

Mean-\ 
Standard deviation-a 
COV 


12 


12 


12 


0.818 


0.718 


0.833 


0.236 


0.322 


0.201 


0.289 


0.449 


0.241 


$ (FOSM) 


p=2.33 


0.47 


0.29 


0.53 


P=3.0 


0.37 


0.21 


0.42 


$ (FORM) 


p-2.33 


0.527 


0.319 


0.598 


p=3.0 


0.431 


0.241 


0.50 



98 



5.3.3 Resistance Factor for Concrete Piles in Mixed soil for Different Locations 

The resistance factor calibration from all 85 data for concrete in mixed soil by using 
different static method are showed in table 5.6a, from Florida and Louisiana data only is 
showed in table 5.6b and 5.6c 



Table 5.6a Resistance Factors for Concrete Piles in Mixed Soil 



Method 


Tomlinson 
Nordlund 
Thurman 


API 
Nordlund 
Thurman 


p 

Thurman 


Schmertmann 


SPT 


CPT 


Number of Cases-N 

Mean-\ 
Standard deviation-a 
COV 


34 


85 


85 


74 


32 


1.00 


0.88 


0.93 


1.97 


0.90 


0.52 


0.47 


0.55 


1.21 


0.35 


0.52 


0.54 


0.59 


0.61 


0.39 


$ (FOSM) 


p=2.33 


0.35 


0.30 


0.28 


0.57 


0.42 


p=3.0 


0.25 


0.21 


0.19 


0.38 


0.31 


$ (FORM) 


p=2.33 


0.381 


0.348 


0.3 


0.6 


0.45 


p=3.0 


0.275 


0.228 


0.208 


0.41 


0.354 



Table 5.6b Resistance Factors for Concrete Piles in Mixed Soil for Florida Data Only 



Method 


a-Tomlinson 
Nordlund 
Thurman 


a-API 
Nordlund 
Thurman 


P 

Thurman 


Schmertmann 


SPT 


Number of Cases-N 

Mean-\ 
Standard deviation-a 
COV 


12 


42 


42 


55 


0.95 


0.97 


1.11 


1.87 


0.57 


0.52 


0.61 


1.10 


0.60 


0.54 


0.54 


0.59 


$ (FOSM) 


p=2.33 


0.28 


0.33 


0.37 


0.56 


p=3.0 


0.19 


0.23 


0.26 


0.38 


$ (FORM) 


p=2.33 


0.296 


0.352 


0.395 


0.595 


p=3.0 


0.201 


0.253 


0.282 


0.41 



99 



Table 5.6c Resistance Factors for Concrete Piles in Mixed Soil for 



Louisiana Data Only 



Method 


a-Tomlinson 
Nordlund 
Thurman 


a-API 
Nordlund 
Thurman 


P 

Thurman 


Schmertmann 


CPT 


Number of Cases-N 

Mean-\ 
Standard deviation-a 
COV 


16 


31 


31 


25 


1.09 


0.68 


0.64 


0.87 


0.52 


0.23 


0.16 


0.33 


0.48 


0.34 


0.26 


0.38 


$ (FOSM) 


p=2.33 


0.42 


0.35 


0.39 


0.41 


p=3.0 


0.30 


0.27 


0.31 


0.31 


$ (FORM) 


p=2.33 


0.45 


0.39 


0.446 


0.455 


p=3.0 


0.329 


0.309 


0.371 


0.354 



100 



6. Data Collection from Vietnam 
6.1 Introduction 

Vietnam is the developing country in Southeast Asia. Now in Vietnam, they start to build 
many highways and highrise building to develop the country. When design the deep 
foundations for bridge and building, they still use the allowable stress design (ASD), but 
most of the highways and buildings from the foreigner investors, who require using the 
load resistant factor design (LRFD). For this reason, this research collected soil profile 
and static and dynamic load tests for driven pile and drilled shafts in North, Central and 
South of Vietnam to calibrate the first LRFD for deep foundation in Vietnam In this 
study, Vietnam is divided into three regions: North, South and Central, as shown in 
Figure 6.1 




Figure 6.1 Vietnamese Map 



101 



Each region is divided into mountain, alluvia plain and coastal. Most driven pile and 
drilled shaft load test data are from cities in the Red River delta in the North, such as 
Hanoi, Hai Phong and Hai Duong, in the Mekong River Delta in the South, such as Sai 
Gon, Vung Tau, and along the Central coast, such as Vinh, Hue, Danang. Most highways, 
high rises are located in these areas. 275 static load tests for driven piles and 92 static 
load tests for drilled shafts have been collected from Vietnam. Each set of pile test data 
also comes with detailed soil profile. Tables E-1 and E-2 in Appendix E show the data 
collected. 



6.2 General description of Vietnam geology 
6.2.1 North Vietnam 

This region is characterized by large formations of Red River depositional units of clay, 
sand, very soft clay, soft sandy clay and clayey sand, the entire region has the soft soil. 
Table 6.1 provides the general stratification of the sub-soils North Vietnam, and Table 
6.2 gives the average properties of each soil type. 

Figure 6.2 shows the six regions including A, B, C, D, E, F which have different 
depth of the gravel layer in Hanoi. The depth gravel layer is very important factor to 



determine the depth of drilled 


shaft. 






The depth of gravel in 


region A: 


h< 


30m 


The depth of gravel in 


region B: 


h = 


30-35m 


The depth of gravel in 


region C: 


h = 


35-40m 


The depth of gravel in 


region D: 


h = 


40-45m 


The depth of gravel in 


region E: 


h = 


45-50m 


The depth of gravel in 


region F: 


h>50m 



102 



Table 6. 1 General soil profile in North Vietnam 



No 




Thickness 
(m) 




Soil Layer 


1 




0.3-6 


1 d 


\ii^v\f Finf^ ^anH 


1b 


MiiHrlv Sanrlv ITIIpiv 


1c 


^_/IC4 yCy wQI \\A 


2 


/////// KV////// 


0.3-8 


2 


wui luy v^iQy 


3 




0.3-6 




v_'iciy cy 


4 




10-19 


4a 1 


^^1llH^I\/ Pf^at 
iviuuuy icai 




4a2 


Miidriv niav 

iviuuuy i^iciy 


4b 


Miirlrlv F^anrlv Olav 
iviuuuy o d 1 luy v^iciy 


4c 


MiiHHv Plavpv ^3nH 
iviuuuy uiciycy vJcii lu 


5 


— \ ^ ^ ^ 


10-12 




Finp S^^nd 

1 II IC OCll lU 


5b 


'■-'iciycy ooi \\A 






10-15 


5c 


Coble 


6 




2-18.5 


6a 


Olflv ^miilti rnlnr^ 




6b 


Clay (gray) 


7 




0.6-4.5 


7 


Sandy Clay 


8 




1-10 


8a 


Muddy Clay 


8b 


Muddy Sandy Clay 




8c 


Muddy Clayey Sand 


9 




0.5-0.8 


9 


Clayey Sand 


10 




0.5-40 


10 


Medium to Coarse Sand 


11 




10-30 


11 


Gravel, Coble 


12 






12 


Bed rock 



103 



Table 6.2 Mean Values Properties of Each Soil Type North Vietnam 







<0.005mm 
(%) 


VV /O J 


"Vwet 

(g/cm^) 


Tsolid 

(g/cm^) 


7dry 

(g/cm') 




O I/O) 


LL 


PI 


degree 


C 

(kg/cm^) 


la 


Very Fine Sand 


- 


30 


1.82 


2.7 


1.4 


0.93 


87.5 






27 


0.08 


lb 


Muddy Sandy Clay 


17 


44 


1.7 


2.69 


1.18 


1.26 


92.5 


37 


13 


14 


0.01 


Ic 


Clayey Sand 


6 


28 


1.82 


2.67 


1.42 


0.88 


85.5 


27 


6 


19 


0.07 


2 


Sandy Clay 


18 


29 


1.88 


2.71 


1.46 


0.85 


91.5 


36 


14 


15 


0.24 


3 


Clay 


40 


33 


1.85 


2.71 


1.39 


0.95 


94.3 


44 


21 


12 


0.38 


4a 1 


Muddy Peat 


38 


76 


1.49 


2.69 


0.85 


2.07 


95.6 


60 


23 


6 


0.14 


4a2 


Muddy Clay 


45 


59 


1.65 


2.7 


1.04 


1.6 


99.5 


51 


25 


8 


0.11 


4b 


Muddy Sandy Clay 


23 


42 


1.73 


2.69 


1.22 


1.2 


93.8 


37 


13 


16 


0.05 


4c 


Muddy Clayey Sand 


7 


36 


1.78 


2.69 


1.31 


1.05 


92.2 


32 


6 


19 


0.03 


5a 


Fine Sand 


- 


26 


1.81 


2.67 


1.46 


0.83 


84 






28 


0.04 


5b 


Clayey Sand 


6 


29 


1.85 


2.68 


1.14 


0.87 


85.8 


27 


7 


20 


0.08 


5c 


Coble 


- 


- 


- 


- 


- 


- 


- 


- 


- 


- 


- 


6a 


Clay (multi color) 


25 


32 


1.86 


2.72 


1.41 


0.93 


93.5 


38 


16 


13 


0.19 


6b 


Clay (gray) 


44 


42 


1.87 


2.72 


1.32 


1 


100 


46 


21 


10 


0.22 


7 


Sandy Clay 


21 


28 


1.85 


2.7 


1.48 


0.83 


91.5 


32 


13 


15 


0.16 


8a 


Muddy Clay 


42 


62 


1.58 


2.63 


0.97 


1.71 


94.8 


55 


24 


11 


0.16 


8b 


Muddy Sandy Clay 


22 


43 


1.74 


2.69 


1.22 


1.21 


95.7 


37 


12 


17 


0.09 


8c 


Muddy Clayey Sand 


8 


39 


1.84 


2.7 


1.32 


1.04 


100 


32 


5 


25 


0.05 


9 


Clayey Sand 


9 


29 


1.85 


2.67 


1.43 


0.86 


90 


28 


5 


27 


0.1 


10 


Medium to Coarse Sand 




26 


1.87 


2.67 


1.19 


0.8 


86.6 






33 


0.02 



104 




105 



6.2.2 South Vietnam 

This region is characterized by low reUef and large formations of Mekong River 
depositional units of soft soil, including: clay, sand, very soft clay, and soft clayey sand 
clay in the upper layer, coarse sand to gravel in the lower layer underlain by moderately 
to highly weathered bedrock. The thickness of soft soil usually ranges from 3m to 30 m, 
however, in some areas it can be as thick as 300m. The soft soil stratification in this 
region starts with 0.5 to 1.5m of top soil, below which are inorganic clay, organic clay, 
very soft clay, soft clayey sand, and the lacustrine clay with interbeded layers of thin sand 
and clay. The thickness of organic layers range from 3m to 4m in Long An, from 9 to 
10m in Thach Anh, Hau Giang and froml8-20m in Long Phu, Hau Giang. This layer has 
very high moisture content, 40% to 70% in clay with 2% to 8% organic materials. Table 
6.3a and 6.3b summarize the properties of this layer. The nonorganic clay usually 3-4m 
below the surface in Long An, 9- 10m in Thach Anh, Hau Giang, 15-16 m in Vinh Qui, 
Tan Long, Hau Giang, 25-26m in My Thanh, Hau Giang, and much deeper near the 
coastal margin. Table 6.4a and 6.4b summarize the properties of this layer. Between 
organic clay and inorganic clay is a sandy clay with thickness about 3 to 5m. The water 
table is at 0.5m to 2m below the ground surface. 



Table 6.3a Properties of Organic Clay Layer in South Vietnam 



Moisture content - co 


50-100% (some area co >100%) 


Liquid limit - col 


50-100% 


Plastic Limit - cop 


20-70% 


Void Ratio - e 


1.2-3.0 (some area e>3.0) 


Unit Weight - 7w 


1.35-1.65 gW 


Dry Unit Weight - 7c 


0.64-0.95 gW 



106 



Table 6.3 b Friction Angle and Cohesion of Organic Clay Layer in South Vietnam 



Void ration - e 


1.2-2.0 


1.2-2.0 


1.4-3.0 


1.4-4.0 


1.4-4.0 


Mean of cj) 


10° 


9° 


8° 


7° 


5° 


STD of(t) 


1°45' 


rso' 


ri2' 


1°15' 


r30' 


Mean of C (KgW) 


0.12 


0.10 


0.08 


0.06 


0.05 


STD ofC(KgW) 


0.02 


0.03 


0.02 


0.02 


0.02 



Table 6.4a Properties of Non-Organic Clay Layer in South Vietnam 



Moisture content - co 


22-55% (some area o) >100%) 


Liquid limit - col 


40-65% 


Plastic Limit - cop 


20-30% 


Void Ratio - e 


0.7-1.5 (some area e>3.0) 


Unit Weight - 7w 


1.65-1.95 gW 


Dry Unit Weight - 7c 


1.05-1.55 gW 



Table 6.4 b Friction Angle and Cohesion of Inorganic Clay Layer in South Vietnam 



Void ratio e 


0.75-1.0 


0.85-1.2 


0.85-1.2 


1.1 - 1.4 


1.2-1.5 


Mean of cj) 


17° 


13° 


11° 


9°30' 


8°30' 


STD of (t) 


2°12' 


r45' 


3° 


ri2' 


9°45' 


Mean of C (Kg/cm') 


0.28 


0.22 


0.18 


0.15 


0.10 


STD of C (Kg/cm') 


0.03 


0.04 


0.04 


0.04 


0.03 



6.2.3 Central Vietnam 

This region is characterized by low relief and large formations of shallow marine 
depositional units of soft soil, including fine sand, sandy clay and clay in the upper layer, 
coarse sand to gravel in the lower layer underlain by moderately to highly weathered 
bedrock. The thickness of upper layer ranges from 15m to 40m with SPT blow count, N, 
from 2 to 15 and the moisture content is very high from 35 to 70%. The lower layer has 



107 



higher SPT blow count from 20 to 45 or higher with the thickness of 4m to 10m. This 
layer is good for resting the tip of driven piles and drilled shafts. 

6.3 Static Load Tests and Soil Profile from a site in Vietnam 

The name of this project is Red River Shipyard and the location of project in Hoang Mai- 
Hanoi. Figures 6. 1, 6.2a, 6.2b, 6.2c, 6.2d show the site plan and four boring logs for this 
project. Tables 6.5, 6.6 and 6.7 show the summary of SPT and the properties of each soil 
layer. Figures 6.3a, 6.3b, 6.3c, 6.3d and 6.3e show static load test data for 5 (350mm 
x350mm) prestressed concrete piles. As can be seen, all load tests were carried out to a 
vertical load twice the design capacities, instead of failure. Thus, Chin's method was used 
to extend the load settlement curve in an attempt to estimate ultimate capacities. 




Figure 6.2 Red River Shipyard Project Site Plan 



108 



Table 6.5 Summary SPT value of each Layer 



No 


Layer 


Soil 
Type 


A vpra OP 

-TV V u.^^ 

Thickness 
of Layer 
(m) 


NSPT 


Number 
of SPT 
tests 


Max 


Mean 


Min 


1 


Layer la 




0.83 


- 


- 


- 


- 


2 


Layer lb 




0.38 


- 


- 


- 


- 


3 


Layer 2 


CL 


2.13 


4 


3 


3 


6 


4 


Layer 3 


CL 


7.50 


7 


5 


5 


6 


5 


Layer 4 


SC 


4.86 


9 


7 


6 


17 


6 


Layer 5 


CL 


4.50 


5 


3 


3 


14 


7 


Layer 6 


SC 


7.48 


9 


7 


5 


24 


8 


Layer 7 


SC 


10.49 


29 


25 


11 


40 


9 


Layer 8 


SP 


2.62 


28 


22 


20 


10 


10 


Layer 9 


CL 


2.80 


8 


7 


6 


4 


11 


Layer 10 


CL 


4.30 


14 


11 


11 


9 


12 


Layer 1 1 


SC 




42 


34 


30 


24 



Table 6.6 Summary of Soil Properties of Clay Layer 



Properties 


Unit 


Layer 


Layer 2 


Layer 3 


Layer 5 


Layer 9 


Layer 10 


5.0-2.0 (mm) 


% 










3.2 


2.0-1.0 (mm) 


% 


0.3 




1.1 




1.9 


1.0-0.5 (mm) 


% 


1.3 


1.0 


2.8 


1.6 


2.1 


0.5-0.25 (mm) 


% 


4.9 


4.4 


5.9 


3.4 


4.1 


0.25-0.1 (mm) 


% 


21.2 


8.2 


22.7 


7.4 


6.8 


0.1-0.05 (mm) 


% 


22.7 


13.1 


21.5 


16.5 


13.0 


0.05-0.01(mm) 


% 


25.2 


34.6 


23.4 


26.2 


27.3 


0.01-0.005(mm) 


% 


15.6 


23.8 


15.0 


21.0 


21.3 


<0.005 (mm) 


% 


9.2 


15.3 


8.9 


24.6 


25.3 


W 


% 


40.8 


28.4 


29.0 


29.7 


26.4 


LL 


% 


43.9 


33.4 


30.8 


36.1 


35.2 


PL 


% 


28.1 


19.61 


20.5 


20.8 


19.8 


PI 


% 


15.8 


13.8 


10.2 


15.3 


15.4 


Ywet 


g/cm^ 


1.72 


1.81 


1.72 


1.93 


1.94 



109 



Table 6.6 (cont.) 



Ydrv 


3 

g/cm 


1.22 


1.40 


1.33 


1.49 


1.53 


Ysolid 


g/cm 


2.67 


2.69 


2.65 


2.73 


2.72 


n 


% 


54.3 


47.8 


49.8 


45.4 


43.7 


s 




1.187 


0.915 


0.994 


0.830 


0.777 


S 


% 


91.8 


83.5 


77.5 


97.6 


92.4 


C 


kG/cm^ 


0.045 


0.196 


0.083 


0.139 


0.259 






6''55' 


11*'57' 


9°10' 


10°52' 




XO.25 


kG/cm^ 


0.077 


0.236 


0.134 


0.077 




XO.5 


kG/cm^ 


0.103 


0.319 


0.167 


0.245 


0.391 


XO.75 


kG/cm^ 


0.137 




0.232 






Xl.O 


kG/cm^ 




0.399 




0.298 


0.506 


X2.O 


kG/cm^ 








0.710 


0.768 



Table 6.7 Summary of Soil Properties of Sand Layer 



Properties 


Unit 


Layer 


Layer 4 


Layer 6 


Layer 7 


Layer 8 


Layer 1 1 


20.0-10.0 (mm) 


% 








16.8 




10.0-5.0 (mm) 


% 








31.7 




5.0-2.0 (mm) 


% 








13.6 




2.0-1.0 (mm) 


% 






1.1 


4.4 




1.0-0.5 (mm) 


% 




2.4 


2.8 


5.2 


0.5 


0.5-0.25 (mm) 


% 


2.9 


4.4 


5.0 


4.2 


2.3 


0.25-0.1 (mm) 


% 


11.8 


21.0 


57.0 


4.1 


18.7 


0.1-0.05 (mm) 


% 


80.3 


69.7 


33.6 


21.3 


74.3 


<0.05 (mm) 


% 


5.3 


4.6 


3.4 


2.2 


4.9 


0.01-0.005 (mm) 


% 












<0.005 (mm) 


% 












Ywet 


g/cm^ 


1.23 


1.23 


1.33 




1.26 


Ydry 


g/cm^ 


1.47 


1.46 


1.48 




1.46 


Ysolid 


g/cm^ 


2.67 


2.67 


2.68 


2.68 


2.70 


n 


% 
















1.176 


1.165 


1.010 




1.126 






0.818 


0.825 


0.811 




0.825 



110 





1 \ \ 

-| -r 

^^^i^-""^"^-! \ ■ 




♦ Static Load Test Data 
Chin's Method 


A _l _L 
L \ \ \ \ 



10 15 20 

Settlement (mm) 



I 



0.1 
0.09 
0.08 
0.07 
0.06 
0.05 
0.04 
0.03 
0.02 
0.01 




y = 0.0055X + 0.0426 
R2 = 0.812 



4 6 

Settlement (mm) 



Figure 6.4a Static Load Test Data and Chin's Method for A5-2 (350x350) Concrete Pile 



100 




♦ Static Load Test Data - - 
Chin's Method 



0.09 q 
0.08- 
0.07. 
0.06. 
0.05. 
0.04. 
0.03. 
0.02. 
0.01 . 
0. 







y = 0.0049X + 0.042 
= 0.863 



Settlement (mm) 



3 4 5 

Settlement (mm) 



Figure 6.4b Static Load Test Data and Chin's Method for Al-5 (350x350) Concrete Pile 




111 




Figure 6.4d Static Load Test Data and Chin's Method for B5-2 (350x350) Concrete Pile 




Figure 6.4e Static Load Test Data and Chin's Method for BlO-2 (350x350) Concrete Pile 



112 



7. Calibration Resistant Factors for Driven Piles in Vietnam 

In this chapter, resistance factors for driven piles in Vietnam are developed for 
different statics methods. Calibration of the resistance factors for each analysis 
method is presented separately and discussed in detail, including histograms and 
frequency distribution for each case attained using database was collected in 
Vietnam by author. For the resistance factors corresponding to a wide range of 
target reliability indices, a sensitivity analysis is considered in order to provide the 
designer the freedom to select and determine the degree of conservatism in the 
design. Efficiency factors are also provided to appropriately compare the 
economy of different methods. Equivalent factors of safety were back calculated 
from the developed LRFD resistance factors to compare the ASD approach and 
determine the percentage of gain in the pile capacity when using the LRFD 
approach. All the regionally developed resistance factors are thus compared with 
the current design specifications. 

7.1 Procedure to Calibrate Resistance Factors for Driven Piles 

Collect the static load tests and soil profile for driven piles in North, Central and 
South Vietnam. 

Calculate the nominal capacity by using different methods 

Interpret the static load tests to find the real capacity of driven piles by using the 

Chin's method and Davission's method. 

Calculate the bias factor = Rmi / Rni 

Calculate the mean, X^, and the coefficient of variation, COV, of the random 
series Xyh. 

Calibrate the resistance factor by using First Order Second Method (FORM), First 
Order Reliability Method (FORM) and Monte Carlo simulation 



113 



7.2 Collection of Driven Piles in Vietnam 

The calibration resistance factor process for driven piles in Vietnam requires an 
extensive data base. From 2008 to 2012 the author collected 275 static load tests 
and soil profiles for driven pile from North, Central and South of Vietnam. The 
hst of all piles including locations, depth and cross section of piles can be found 
in table El in appendix E. Almost data for driven pile from the North Plain (NP), 
Central Plain (CP) and South Plain (SP) of Vietnam. 

7.3 Measurement capacity of driven piles 

Chin method, 1" settlement's criterion and Davission's criterion were used to 
interpret the static load test data for driven pile in North, Central and South of 
Vietnam and the result shown detail in Table El in appendix E. The Fig 7.1a and 
Fig 7.1b show the relationship among 80% Chin method, 1" settlement and 
Davission's criterion for 275 driven piles statics load test. Davission's criterion is 
used to determine the capacity for the driven piles, since Davission's capacity is 
closed to both 80% Chin and 1" settlement's capacity. 

7.4 Nominal Capacity of driven piles 

As mentioned in Chapter 3, eight different pile static analysis methods were used 
for predicting the design nominal capacity of concrete piles in this research. These 
methods included: a- Tomlinson, a-API, A,, P, Nordlund, Thurman, Meyerhof 
SPT, and Shmertmann SPT method. Thea, P, X, Nordlund and Thurman method 
use the friction angle (p and/or the undrained shear strength Su or the over- 
consolidation ratio OCR, but most of the soil data from the database are from SPT 
tests. Therefore, the soil parameters were mainly calculated based on the 
corrected SPT N-values and using the soil correlations previously mentioned in 
Chapter 3. Spreadsheets were created for each method in order to predict the 
capacity of the 273 concrete piles. 



114 



7.4.1 Nominal Capacity of Concrete Piles in Cohesionless Soils 

The Nordlund and Thurman method were used to get the nominal capacity of 
driven pile in sand by using the correlation between Nspt and the friction angle of 
sand by Peck, Hanson & Thombum and Schmertmann and the result can be found 
in table E-3 in appendix E. Fig 7.1a and 7. lb show the prediction capacity by 
using the correlation from Peck is closer to Davission's capacity than 
Schmertmann Fig 7.1c and 7. Id show the prediction capacity from empirical 
method including Schmertmann SPT and Meyerhof SPT and measure capacity are 
closed 



80% Chin's Vs Davission Capacity 




100 200 300 400 500 

Davission's Capacity 



Figure 7.1a Measure Capacity Davisson's versus 80% Chin Method 



115 



500 



400 



>-300 

'u 

Q. 

^ 200 



100 



1" Vs Davission Capacity 






















































































































































































































































































































































































V : 

-f— 


— Vj 




Lx 














♦ 




z 




















































































































































































































































































• 
























































































































































































♦ 















































































































































































































































































































































































100 200 300 

Davission's Capacity 



400 



500 



Figure 7.1b Measure Capacity Davisson's versus 1" settlement 



Nordlund method Vs Davission Capacity 



800 
700 
-g 600 
^|500 
i £400 
o i 300 

-e- 

200 
100 














































































































































































































































— 




































































































































































































^ 

- y = 


1.58 


bx- 












































= n q 


ts- 












































































































































































-1 




A 


-V 




1.5 


50 




































M 








— f 


2 _ 

































































































































































































































♦ North 
■ South 



Linear 
(North) 



■ Linear 
(South) 



100 200 300 

Davission's Capacity 



400 



500 



Figures 7.2a: Prediction Capacity using Nordlund method vs. Measure Capacity of 
Concrete Piles in Cohesionless Soils (North and South of Vietnam) 



116 



3 l/l 



o o 



1400 
1200 
1000 
800 
600 
400 
200 




Nordlund and Thurman method 



m 



2^ 08 It 



64 



«7t 



100 



200 300 
Davission's Capacity 



400 



♦ North 
■ South 



500 



Figures 7.2b: Prediction Capacity using Nordlund method vs. Measure Capacity of 
Concrete Piles in Cohesionless Soils (North and South of Vietnam) 



Schmertmann SPTVs Davission Capacity 



CO 
C 

c 



450 
400 
350 
300 
250 
200 
150 
100 
50 
































































































































V 


- r 




























































































1 
































































































*- 
















































































































































































































































































































































■ 




















































— ^ 








m 






















































































• m 


— 1 






























































































•* 





















































































































































































100 



200 300 
Davission's Capacity 



400 



500 



Figures 7.2c: Prediction Capacity using Schmertmann SPT method vs. Measure Capacity 
of Concrete Piles in Cohesionless Soils (North, Central and South of Vietnam) 



117 



400 
350 
300 



S: 250 



200 
150 
100 
50 




Meyhoft SPT Vs Davission Capacity 



































































































































-y- 


=-0 


n r 














































-K 




















































- 






































































































— J 
— ^ 


t 


























































































3 












































































































































m 




































































































- y 














































-2- 


-0 











































































































































































































































































100 200 300 

Davission's Capacity 



400 



500 



♦ North 



Figures 7. 2d: Prediction Capacity using Meyerhof SPT method vs. Measure Capacity of 
Concrete Piles in Cohesionless Soils (North, Central and South of Vietnam) 



7.4.2 Nominal Capacity of Concrete Piles in Cohesive Soils 

The a-Tomlinson method, a-API method, X method, P-Burland, Schmertmann 
SPT method were used to get the nominal capacity of driven pile in cohesive soil 
by using the correlation between Nspt and the un-drain shear strength Su of clay 
by Terzaghi and Peck (1967) and Hara (1974). The prediction capacity of driven 
piles in cohesive soil can be founded in table E-3 in appendix E. Fig 7.2a to 7.2g 
show the prediction capacity by using the correlation between Nspt and Su from 
Terzaghi and Peck is underestimate and from Hara is over estimate with all 
method using in calculate the nominal capacity for driven piles in cohesive soil. 
Fig 7.2h shows the prediction capacity from empirical Schmertmann SPT method 
is closed to measure capacity 

7.4.3 Nominal Capacity of Concrete Piles in Mixed Soils 

Seven different pile static analysis methods were used for predicting nominal 
capacity of concrete piles in mixed soil including: a-Tomlinson, a-API, A,, P- 
Burland, Nordlund, Thurman, Schmertmann SPT method by using the correlation 



118 



between Nspt and the un-drain shear strength Su of clay by Terzaghi and Peck 
(1967) or Hara (1974) and friction angle of sand by Peck, Hanson and Thomburn 
or Schmertmann. The predicted capacity of driven piles in mixed soil is in table 
E-5 in appendix E. Fig 7.3a to 7.2g show the prediction capacity by using the 
correlation friction angle from Peck, Hanson and Thornbum is closer to measure 
capacity and from Schmertmann is over estimate. 



300 



250 



a-Tomlinson method (Su:Terzaghi-Peck ) 



T3 
C 

_2 

T3 
i_ 
O 

T3 
C 

TO 

C 

o 



200 



150 



100 



50 













































































































































































































































































































































































































































































r 




86 


5x 
























































H 




54 


























































































































































































£ 










































































































i: 






















y 








; 


















-=- 
































F 






















































































1 




= -( 


) 5 













































































































































































































































a- 


























































y = 













































































































































































































































































































































































































































▲ 
♦ 

X 



North 

South 

Central 

Total 

Linear 
(North) 

- Linear 
(South) 

- Linear 
(Central] 

■ Linear 
(Total) 



50 100 150 

Davission's Capacity 



200 



250 



300 



Figures 7.3a: Prediction Capacity using a-Tomlinson method vs. Measure Capacity of 
Concrete Piles in Cohesive Soils- Su from Terzaghi-Peck in North, Central and South of 
Vietnam 



119 



300 



250 



T3 

J 200 

T3 
O 



150 



100 



50 



a-Tomlinson method (Su: Hara) 





























































































































































— V 




IT! 


55 




























































1-' 


^'-^ 














































■ 


-f 




fO 














































-I 
















1 


If 


Ix 








































- 














r 


= 0.9 






















































































































































































































































































































































































■ 






' ■ 








IK 








































































































































































































































































































































-y. 


= ( 




)1 


< 
























































































k 








E 














K 




U. 




r 


































































































































































































-1 







































































































































































































































50 



100 . 150 ^ . 200 
Davission s Capacity 



250 



300 



■ North 

▲ South 

♦ Central 

X Total 

Linear 

(North) 
Linear 

(South) 
Linear 

(Central) 
Linear 

(Total) 



Figures 7.3b: Prediction Capacity using a-Tomlinson method vs. Measure Capacity of 
Concrete Piles in Cohesive Soils-Su from Hara in North, Central and South of Vietnam 



C 

T3 
O 



O 
H 
B 



300 



250 



200 



o 150 



100 



50 



a-API method (Su: Terzaghi-Peck) 





























































































































































































































































































































































































































































































































































































































































































































































































































y 


= 


n ■ 


IS 


IX- 


































































y 










































H 


z _ 


U 


/: 


/ 




F 


-I 
















































































































H 
























H 




S5 


K- 


















































-R 


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1 




































































































































































































■ 1 
































































■ 






















































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4i 


b> 


































■< 








































































— 




©: 































































































































































































50 100 150 200 

Davisslon's Capacity 



250 



North 



▲ South 



Central 



Linear 
(North) 



Linear 

(South) 



■ Linear 
(Central; 



300 



Figures 7.3c: Prediction Capacity using a-API method vs. Measure Capacity of Concrete Piles in 
Cohesive Soils-Su from Terzaghi-Peck in North, Central and South of Vietnam 



120 



a-API method (Su: Hara ) 




250 - 






























































■ North 

^ South 

♦ Central 

Linear 

(North) 

Linear 

(South) 

Linear 
















































































































































■ 












¥- 


: 1 


n 


-U 


L — 






































n 






































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— 


=3 


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n/Nordlu 

n C 
































y 








































































































■ 


/ 

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(Central) 

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C 


) 5 


1( 
D< 


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avission's Ca 


50 2( 

pacity 


DO 21 


50 3C 



Figures 7.3d: Prediction Capacity using a-API method vs. Measure Capacity of 
Concrete Piles in Cohesive Soils-Su from Hara in North, Central and South of Vietnam 



300 



250 



T3 

J 200 

T3 
i_ 
O 



§ 150 



100 



50 



X-Nordlund (Su: Terzaghi-Peck ) 





























































































































































































































































































































































































































































































































































































































































































































































































































n 


<- 






i 




































































































R 


! _ 


n 


ii 




















































































— ? 








kr 














































































A 






























y 






J4 


( 






































































































m 




-R 


































































































































































































-y- 
























































R' 




).( 

































































































































































































































































Linear 

(South) 



50 100 150 200 

Davission's Capacity 



250 



300 



Figures 7.3e: Prediction Capacity using X method vs. Measure Capacity of Concrete Piles in 
Cohesive Soils-Su from Terzaghi and Peck in North, Central and South of Vietnam 



121 



300 



250 



§ 200 
o 



c 150 
o 



100 



50 



A,-Nordlund (Su Hara ) 





















































































■ 


- 


























































■ 












































































































































































































































I 










-7— 














■ — 




k 








































— 7 
/ 












' — 




































1 > 






















































y - J..- 




X- 
















-A 


■= 1 


























5-^ 


6 




z ■ 






























































V 










b 


























- 





















































































































/ 










n 
























































































































































































































* 


















he 
















































-1 








-Q- 




























































































■ 




















































































































































































































































































m 













































































































































































































































50 100 150 200 

Davission's Capacity 



250 



North 



▲ South 



♦ Central 



Linear 
(North) 



■ Linear 
(South) 

■ Linear 
(Central; 



300 



Figures 7.3f: Prediction Capacity using A. method vs. Measure Capacity of Concrete Piles in 
Cohesive Soils-Su from Hara (North, Central and South of Vietnam) 



300 



250 



T3 

J 200 

T3 



C 

o 



o 

H 
B 



150 



100 



50 



P method 















































































































































































































































































































































































































































































































































































































> 








































































































- 












— 












































-1 












— > 










k 
























-k 
















F 
















= f 


8 


?1 
















































































it 










-I 














K 




-4 


bL 


. 






































































- i.' 




■ 
















































-E 


2 = n 


,689. 








w 










































































































-St- 






















• 




t 




















































































































































— 7 




































































































































= n 7 





























































































































































































































































North 



South 



Central 



Linear 
(North) 



Linear 

(South) 



■ Linear 
(Central) 



50 100 150 200 

Davission's Capacity 



250 



300 



Figures 7.3g: Prediction Capacity using p method vs. Measure Capacity of Concrete Piles in 
Cohesive Soils (North, Central and South of Vietnam) 



122 



300 



250 



200 



§ 150 



100 



50 



Schmertmann SPT 













































































































































































































































































































































































































































































































































U. 


'8. 


Ix 






















































2 . 


























































-f 








ij 




































i 


- 






































































































y ■ 


= 1 






: J_ 








_ 








































nl 




























> 


































V. 




























































































































— 

























































-ft 


















































J 














V = 


-- 0.7 
































H 




















































1^ ^<^* 
















J.; 




























































































■ 
























































1 


1 



















































































































































































































































































































































■ North 

▲ South 
♦ Central 



Linear 

(North) 
■ Linear 

(South) 
• Linear 

(Central) 



50 100 150 200 

Davission's Capacity 



250 



300 



Figures 7.3h: Prediction Capacity using Schmertmann SPT method vs. Measure Capacity of 
Concrete Piles in Cohesive Soils (North, Central and South of Vietnam) 



a-Tomlinson-Nordlund (Su: Terzaghi-Peck; (j): Peck, Hanson & Thornburn) 

800 I I I I I 



700 



600 



500 



§ 400 




mi 



2ix 



100 200 300 400 

Davission's Capacity 



500 



600 



■ North 

▲ South 
♦ Central 



Linear 

(North) 
■ Linear 

(South) 
• Linear 

(Central) 



700 



Figures 7.4al : Prediction Capacity using a-Tomlinson, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils- Su from T-P, (p from P-H-T (North, Central and South 
of Vietnam) 



123 



a-Tomlinson-Nordlund (Su Hara; Peck, Hanson & Thombum) 




100 200 300 400 500 
Davission's Capacity 



600 



■ 


North 




South 


♦ 


Central 




Linear 




(North) 




- Linear 




(South) 




- Linear 




(Central) 



700 



Figures 7.4a2: Prediction Capacity using a-Tomlinson, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils - Su from Hara, (p from P-}i-T(North, Central and 
South of Vietnam) 



1200 



1000 



a-Tomlinson-Nordlund (Su: Terzaghi & Peck; (j): Schmertmann ) 



-a 
o 



800 



600 



400 



200 













































































































































































■ 


















































































































































































































H 


1- 








































































































































■ 




























y 




































A 


i 














38 


X 




















































t 








y 




1 


4 


















































- 

















/II 




































































✓ 












-k 








































































t- 




















































1 


















































a 




a 












y' 
































































































































































































































































- 


k 






















.1 


8! 


5x 




























































— 
























































































































































































































































































































































































































































































































































k 
















































- 1 































































100 



200 



300 400 500 
Davission's Capacity 



600 



■ North 

t South 

♦ Central 

Linear (North) 

Linear (South) 

Linear (Central) 



700 



Figures 7.4a3: Prediction Capacity using a-Tomlinson, Nordlund, Thurman method vs. 
Measure Capacity of Concrete Piles in Mixed Soils - Su from T-P, cp from Schmertmann (North, 
Central and South of Vietnam) 



124 



1200 



1000 



a-Tomlinson-Nordlund (Su: Hara; ()): Schmertmann) 



800 



"a 
o 



600 



400 



200 









































































































































































■ 
















































































































































































































































































































— 








































■ 




































































i- 






























— 


























r 












■ 




































































- 








= 1.52 
- n a 


2x 




























































y 








































































































































- 


L 






































































































































* 












































































































































































































- ] 


L; 


oi 














































'i 










= n 












































— 


















































































































1 
































































>i 






































































































































































































































































— 















































































































■ 


North 




South 


♦ 


Central 




Linear 




(North) 




- Linear 




(South) 




- Linear 




(Central) 



100 200 300 400 

Davission's Capacity 



500 



600 



700 



Figures 7.4a4: Prediction Capacity using a-Tomlinson, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils - Su from Hara, cp from Schmertmann (North, Central 
and South of Vietnam ) 

a-API-Nordlund (Su: Terzaghi & Peck; Peck, Hanson & Thornburn) 



800 -| 






































































■ North 

A South 
♦ Central 
Linear 












































































































































700 - 
600 - 
































■ 
























/> 










































- 














































































— , 


L 








<' 


















































1- 




































E 500 - 
















/ = 












t 


— 
















— 3 




































- 
























y 


= 1.: 


204) 














ordlu 
















































R 







7 




— 
















































































API/N 

1 


















































































— 


L 












/> 












































































































B 300 - 
















r" 






■ 


»^ 


9- 






F 


' d 


-tl 
= 


0. 


55 


7 




























200 - 
100 - 
- 


mil 


mil 


mil 


























































(North) 
Linear 

(South) 
Linear 




■ 






















































ir 










i- 


























































- 
















































(Central) 

































































100 200 300 400 500 600 700 

Davission's Capacity 



Figures 7.4b 1 Prediction Capacity using a- API, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils-Su from T-P, cp from P,H &T(North, Central and South 
of Vietnam) 



125 



a-API-Nordlund (Su Hara; (j): Peck, Hanson &Thurnburn) 



900 
800 
700 



600 
500 



51 400 

< 

a 

300 



200 
100 





131 



North 



▲ South 



♦ Central 



Linear 

(North) 

Linear 

(South) 



■ Linear 
(Central' 



100 



200 300 400 500 
Davission's Capacity 



600 



700 



Figures 7.4b2: Prediction Capacity using a-API, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils-Su from Hara, (p from P,H &T (North, Central and 
South of Vietnam) 



a-API-Nordlund (Su: Terzaghi & Peck -cp: Schmertmann ) 



T3 
C 

T3 
i_ 
O 



Q. 

< 



1200 



1000 



800 



600 



400 



200 




■ North 

▲ South 
♦ Central 



Linear 
(North) 
■ Linear 
(South) 
Linear 
(Central) 



100 200 300 400 500 
Davission's Capacity 



600 



700 



Figures 7.4b3: Prediction Capacity using a-API, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils-Su from T-P, (p: from Schmertmann (North, Central 
and South of Vietnam) 



126 



a-API-Nordlund (Su: Hara; cp: Schmertmann ) 



1200 



1000 



800 

c 

° 600 



Q. 

< 

B 400 



200 



































































































































/ 










































1 


1- 
































































- 





- 




















-\t 








-i 


k- 


























































y 

-R 


2 . 




t€ 


M 
































uoox 




























































1 




= 




















































































r — 


















































i 










■7— 












1 


^^ 


4' 


X 














































A 














= 




/ 








































m 


H 








m 














































r 
























































- 




W3 m 

-^1-1 




_ 




■ 


■ 


m 


















































































































-, 

















































■ North 
▲ South 
♦ Central 



Linear 

(North) 

Linear 

(South) 
Linear 

(Central) 



100 200 300 400 500 
Davission's Capacity 



600 



700 



Figures 7.4b4: Prediction Capacity using a-API, Nordlund, Thurman method vs. Measure 
Capacity of Concrete Piles in Mixed Soils-Su: Hara; 9: Schmertmann (North, Central and South 
of Vietnam) 



1-Nordlund (Su: Terzaghi & Peck; Peck, Hanson & Thornburn ) 




■ North 
k South 
♦ Central 

Linear 

(North) 

Linear 

(South) 

Linear 

(Central' 



100 200 300 400 500 
Davission's Capacity 



600 



700 



Figures 7.3cl : Prediction Capacity using A., Nordlund, Thurman method vs. Measure Capacity of 
Concrete Piles in Mixed Soils-Su: Terzaghi & Peck; (j): Peck, Hanson & Thornburn (North, 
Central and South of Vietnam) 



127 



A,-Nordlund (Su: Hara; (j): Peck, Hanson &Thornburn ) 




■ North 

A South 
♦ Central 



Linear 

(North) 

Linear 

(South) 

Linear 

(Central) 



100 200 300 400 500 

Davission's Capacity 



600 



700 



Figures 7.4c2: Prediction Capacity using X, Nordlund, Thurman method vs. Measure Capacity of 
Concrete Piles in Mixed Soils-Su: Hara; (j): Peck, Hanson & Thombum (North, Central and South 
of Vietnam) 



A.-Nordlund (Su: Terzaghi & Peck; cj): Schmertmann) 



T3 
C 

T3 
i_ 
O 



1200 



1000 



800 



600 



400 



200 















































































































































































■ 




































































- 












































































































































■ 








































































































































■ 






































































- 
































































-\ 


t- 


















< 












































I 












v 
































































> _ n 


























































































































1 


If 


?> 


















































































/ 


















































K 




L 


.b 


id 








It 






























































































































































































▲ 
















































































A 




1 


1 




y 














































-k 
































































■ R" = 0.67 


b 














































■ 


i 




i| 












































* 













































































































































































































































































































































■ North 

A South 
♦ Central 



Linear 

(North) 

Linear 

(South) 

Linear 

(Central) 



100 200 300 400 500 

Davission's Capacity 



600 



700 



Figures 7.4c3: Prediction Capacity using A., Nordlund, Thurman method vs. Measure Capacity of 
Concrete Piles in Mixed Soils-Su: Terzaghi& Peck; 9: Schmertmann (North, Central and South 
of Vietnam) 



128 



A-Nordlund (Su: Hara; cj): Schmertmann) 



1200 



1000 



800 

T3 

c 
_2 

"E 600 
o 



400 



200 







































































































































































■ 








































































































































H 


1- 






























































































































































y 








































■ 






















































































_ 










































































M 


r 

L 


























;.009>( 


























































-y- 


































































() 


7- 






























































































r- 


: J 


.fc 




Ix 




































































































































u. 




z 












































~7 


































































— , 
































































































































































































V 
































































































s 




















































i 
























































1 

























































































































































































































































































































































North 



▲ South 



♦ Central 



Linear 
(North) 



100 200 300 400 500 600 700 

Davission's Capacity 



Figures 7.4c4: Prediction Capacity using A., Nordlund, Thurman method vs. Measure Capacity of 
Concrete Piles in Mixed Soils-Su: Hara; 9: Schmertmann (North, Central and South of Vietnam) 



P method ((j): Peck, Hanson, Thornburn) 




• North 
■ South 

▲ Central 



Linear 

(North) 
■ Linear 

(South) 
• Linear 

(Central) 



50 100 150 200 250 300 350 400 

Davission's Capacity 



Figures 7.4dl : Prediction Capacity using p method vs. Measure Capacity of Concrete Piles in 
Mixed Soils-(j): Peck, Hanson, Thombum-(t): Peck, Hanson, Thornburn (North, Central and South 
of Vietnam) 



129 



700 n 


























P 


rr 




't 


h( 


DC 


\ 


(4 


; 


S 


cl 


ir 


ni 


;r 


tr 


n 


ir 


in 


) 
















1 

• North 
■ South 

▲ Central 
Linear 


600 - 






































































- ^ 




D, 

Q- 

J. 












































































































































1 






u 


D 
































































— 
































































V 




r 


7 




X 






































































R 




rt 






7 


























500 - 
"§ 400 - 


































— 














• 










-7 




























































1 


1 








































































— 


w. 
















































+-< 

1. 300 - 






























1- 

1- 




i 














• 








• 






— 




1 




(X 






































1 — 






I' 










-i 










? 


— 
- 




J> 


































■- 




















i 


































200 - 










-i 












( 


> 






























n 


























(North) 
Linear 

(South) 
Linear 














— 




















i 


















































































\ 


- 












h. 






























100 - 


















at 


»*- 






























i 
























































4 












































(Central) 

)0 






























































































n 




i 


1 




1- 
























































■ 


m 


1- 




























■ 








































































































\ 

c 


) 5 











IC 


)0 






[ 


IE 
)a 


50 
vi 


ss 


io 


n 


2C 

s 


)0 

C; 


3P 


a( 


:it 


2^ 
y 


;o 








3C 


)0 








3E 


50 








4C 



Figures 7.4d2: Prediction Capacity using P method vs. Measure Capacity of Concrete Piles in 
Mixed Soils-(j): Schmertmann (North, Central and South of Vietnam) 



Schmertmann SPT Vs Davission Capacity 




♦ North 
■ Central 
▲ South 

Linear 

(North) 

Linear 

(Central) 

Linear 

(South) 



50 100 150 200 250 300 350 

Davission's Capacity 



Figures 7.4el : Prediction Capacity using SPT method vs. Measure Capacity of Concrete Piles in 
Mixed Soils (North, Central and South of Vietnam 



130 



7.5 Calibration of Resistance Factors 

As discussed in Chapter 4, there are tree statistical methods used for the LRFD 
resistance factor calibration including First Order Second Moment (FOSM), First 
Order Reliability Methods (FORM) and other advanced methods, such as the 
Monte Carlo simulation, have been used for performing the reliability analyses 
with assuming a lognormal distribution of the load and resistance Probability 
Density Functions (PDFs).The author conducted the analysis using both the 
FOSM and the FORM methods using the data from NHCRP 507 report and the 
result showed that the difference between FOSM and FORM is relatively small 
(did not exceed 10% on average) as the FOSM provides slightly conservative 
resistance factors. Using the equation 7.1 for FOSM and writing the Matlab 
program by using the theory in chapter 4 for FORM and Monte Carlo simulation 
to find the resistance factor (jjwith the following parameters: dead load factor- Yd = 
1.25, live load factor-yL = 1.75, dead load bias factor-A^jD = 1-08, live load bias 
factor->iQL =1.15, dead load coefficients of variation-COVgD = 0.13 and live load 
coefficients of variation COVql= 0.18. Sine dead to live load ratio QD/QL 
changes from 1-3 and has almost no effect on the resistance factor, this study uses 
QD/QL = 1. 



o J(i+coy,;+coy,/)/(i+coy/) 

<t>= r ^ \ ^ , (7-1) 

V J 

As commented in Chapter 4, the targeted p values in this study were chosen to be 
similar to those used in the 2012 AASHTO-LRFD specifications and the NCHRP 
report 507, i.e., P = 2.33 (Pf = 1%) for redundant pile groups (consisting of five or 
more piles/cap), and P = 3.0 (Pf = 0.1%) for non-redundant pile groups (less than 
five piles/cap). However, the LRFD resistance factors will be calculated herein 
for a wider range of P, providing the freedom of selecting any other target 
reliability and corresponding resistance factors for pile design. 



131 



7.5.1 Resistant factors for driven piles in Sand 

Table 7.1, 7.1a, 7.1b, 7.1c shows the bias factor and the calibration resistance 
factor as well as efficiency factor ((p/A,),equivalent factor of safety to ASD and 
actual mean factor of safety for driven pile in cohesionless soil by different 
method for calculating the nominal capacity in North, Central and South of 
Vietnam. The resistant factors by using FORM method and Monte Carlo 
simulation are almost the same and about 10% higher than FOSM method. Figure 
7.5a and 7.5b is an example of the histogram and frequency distribution of bias 
factor XI and an example of resistant factor calibration for 58 cases of concrete 
piles in Sand using the Nordlund and Thurman method with correlation between 
the friction angle (j) and SPT value buy Peck, Hanson and Thurman by using all 
data for cohesionless soil in Vietnam. The other histograms and fi'equency 
distributions of bias factor: A,l toA,4 and resistant factor calibration: Olto 04 for 
All data. North data, and South data can be found in figure F-Sl-a to F-S4d in 
appendix F 

Table. 7.1 Bias factor X for driven pile in Cohesionless Soil using Nordlund , Shmertmann 
SPT and Mayhoft SPT method with Davission's criterion in North, Center and South of 
Vietnam 





Nordlund 


SPl 




O: Peck, Hanson and 
Thornburn 


0:Schmertmann 


Schmertmann 
SPT 


Mayhoft 
SPT 


U 


X2 


X3 


X4 


NP-Sl 


0.80 


0.49 


0.89 


0.94 


NP-S2 


0.75 


0.46 


0.82 


0.87 


NP-S3 


0.83 


0.51 


0.91 


0.97 


NP-S4 


0.64 


0.41 


0.82 


0.79 


NP-S5 


0.66 


0.42 


0.85 


0.82 


NP-S6 


0.61 


0.39 


0.79 


0.76 


NP-S7 


0.69 


0.44 


0.88 


0.85 


NP-S8 


0.67 


0.43 


0.87 


0.83 


NP-S9 


0.67 


0.42 


0.86 


0.83 


NP-SIO 


0.69 


0.44 


0.89 


0.85 


NP-Sll 


0.70 


0.44 


0.90 


0.86 


NP-S12 


0.63 


0.40 


0.81 


0.78 


NP-Sl 3 


0.70 


0.44 


0.89 


0.86 


NP-S14 


0.69 


0.44 


0.88 


0.85 



132 



Table 7.1 (cont.) 



NP-S15 


0.74 


0.47 


0.95 


0.91 


NP-S16 


0.72 


0.46 


0.92 


0.89 


NP-S17 


0.73 


0.46 


0.93 


0.90 


NP-S18 


0.71 


0.45 


0.91 


0.87 


NP-S19 


0.69 


0.44 


0.89 


0.86 


NP-S20 


0.57 


0.39 


0.92 


0.94 


NP-S21 


0.67 


0.46 


1.09 


1.11 


NP-S22 


0.76 


0.51 


1.23 


1.26 


NP-S23 


0.51 


0.34 


0.82 


0.84 


NP-S24 


0.57 


0.39 


0.93 


0.95 


NP-S25 


0.66 


0.45 


1.08 


1.10 


NP-S26 


0.84 


0.57 


1.38 


1.40 


NP-S27 


0.64 


0.44 


1.05 


1.07 


NP-S28 


0.71 


0.49 


1.16 


1.19 


NP-S29 


0.63 


0.43 


1.03 


1.05 


NP-S30 


0.73 


0.50 


1.19 


1.22 


NP-S31 


0.59 


0.40 


0.96 


0.98 


NP-S32 


0.61 


0.34 


1.21 


1.42 


NP-S33 


0.53 


0.30 


1.04 


1.23 


NP-S34 


0.46 


0.26 


0.91 


1.07 


NP-S35 


1.11 


0.40 


1.10 


1.03 


NP-S36 


1.28 


0.47 


1.27 


1.19 


NP-S37 


1.22 


0.44 


1.20 


1.13 


NP-S38 


1.16 


0.42 


1.15 


1.08 


NP-S39 


1.21 


0.44 


1.19 


1.12 


NP-S40 


0.94 


0.68 


1.15 


1.04 


NP-S41 


1.13 


0.63 


0.81 


0.65 


NP-S42 


1.15 


0.64 


0.82 


0.66 


NP-S43 


1.19 


0.66 


0.85 


0.69 


NP-S44 


1.50 


0.75 


1.80 


1.94 


NP-S45 


1.35 


0.67 


1.62 


1.75 


NP-S46 


1.43 


0.72 


1.72 


1.86 


NP-S47 


0.78 


0.65 


1.83 


2.14 


NP-S48 


0.80 


0.67 


1.88 


2.21 


NP-S49 


0.78 


0.65 


1.81 


2.13 


NP-S50 


0.70 


0.59 


1.64 


1.93 


NP-S51 


1.11 


0.71 


1.05 


0.99 


NP-S52 


1.18 


0.75 


1.12 


1.05 


NP-S53 


1.26 


0.80 


1.19 


1.12 


NP-S54 


1.18 


0.75 


1.12 


1.05 


SP-Sl 


0.76 


0.58 


1.35 


1.80 


SP-S2 


0.84 


0.56 


1.42 


2.09 


SP-S3 


0.58 


0.38 


1.10 


1.02 


SP-S4 


0.46 


0.30 


0.88 


0.90 



133 



LamdalAIISand data 

Normal 

Log normal 




0.5 1 1.5 

Bias Factor 

Fig 7.5a Histogram and frequency distribution of bias factor XI for 58 cases of concrete 
piles in Sand using the Nordlund method (cj): Peck, Hanson and Thornbum) in Vietnam 




3 4 5 

Reliability Index, p 



Fig7.5b Resistant factor calibration for 58 cases of concrete piles in Sand using the 
Nordlund method ((j): Peck, Hanson and Thornbum) in Vietnam 



134 



Table 7.1a Summary of calibration resistance factor for driven pile using Nordlund 
,Shmertmann SPT and Mayhoft SPT method in North, Center and South of Vietnam 





Data from North, Central and South of Vietnam 


Nordlund-Thurman 


SPT 


OPeck, Hanson 
and Thornbum 


Ofrom 
Schmertmann 


OL-ilillCi Lilldllll Ol 1 


Mavhnft SPT 


X\ 


X2 


X3 


X4 


Total 


Mean 


0.83 


0.50 


1.10 


1.13 


58 cases 


Stand 


0.26 


0.13 


0.29 


0.41 




GOV 


0.32 


0.26 


0.27 


0.36 


p =2.33 


FOSM 


0.448 


0.306 


0.662 


0.564 


FORM 


0.490 


0.342 


0.732 


0.610 


Monte"* 


0.493 


0.344 


0.729 


0.607 




0.60 


0.69 


0.66 


0.54 


FS^ 


2.8 


4.0 


1.9 


2.3 


FSxA,^ 


2.3 


2.0 


2.1 


2.6 




FOSM 


0.347 


0.244 


0.527 


0.429 


FORM 


0.390 


0.289 


0.598 


0.470 


Monte 


0.397 


0.290 


0.604 


0.473 


(p/A. 


0.48 


0.58 


0.55 


0.42 


FS 


3.5 


4.7 


2.3 


2.9 


FSxA, 


2.9 


2.4 


2.5 


3.3 


Good result 


good 




good 


good 



1 Efficiency factor 2Equivalent factor of safety to ASD 3 Actual mean factor of safety 4 Monte Carlo simulation 



Table 7. lb Summary of calibration resistance factor for driven piles using Nordlund 
,Shmertmann SPT a nd Mayhoft SPT method in North of Vietnam 





Data from North 


Nordlund-Thurman 


SPT 


OPeck, Hanson 
and Thornbum 


Ofrom 
Schmertmann 


Schmertmann SPT 


Mayhoft SPT 


X\ 


X2 


X3 


X4 


Total 


avera 


0.84 


0.50 


1.09 


1.11 


54 cases 


stand 


0.27 


0.13 


0.30 


0.39 




cov 


0.32 


0.26 


0.27 


0.35 


p =2.33 


FOSM 


0.456 


0.309 


0.652 


0.563 


FORM 


0.490 


0.342 


0.720 


0.603 


Monte 


0.489 


0.343 


0.712 


0.601 




0.58 


0.68 


0.65 


0.54 


FS^ 


3.0 


4.5 


2.1 


2.4 


FSxA.^ 


2.5 


2.2 


2.3 


2.7 


P=3 


FOSM 


0.354 


0.247 


0.517 


0.430 


FORM 


0.395 


0.285 


0.590 


0.700 


Monte 


0.394 


0.287 


0.586 


0.466 


(p/A. 


0.47 


0.57 


0.54 


0.42 


FS 


3.9 


5.6 


2.7 


3.2 


FSxA 


3.3 


2.8 


2.9 


3.5 


Good result 


good 




good 


good 



135 



North South and Central of Vietnam 



■ phi ■phi/lamda lamda 1.10 




12 3 4 



Figure 7.6a Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using Nordlund, Shmertmann SPT and Mayhoft SPT method for Cohesionless 
Soil in Vietnam with P =2.33 



North of Vietnam 

■ phi ■phi/lamda ..lamda 

1.09 1-11 




12 3 4 



Figure 7.6b Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using Nordlund, Shmertmann SPT and Mayhoft SPT method for Cohesionless 
Soil in North of Vietnam with p =2.33 



136 



7.5.2 Resistant factors for driven piles in Clay 

Table 7.2, 7.2a, 7.2b, 7.2c shows the bias factor and the calibration resistance factor 
as well as efficiency factor (cp/A.), equivalent factor of safety to ASD and actual 
mean factor of safety for driven pile in Cohesive Soil by different methods for 
calculating the nominal capacity in North, Central and South of Vietnam. The 
resistant factors by using FORM method and Monte Carlo simulation are almost the 
same and about 10% lower than FOSM method. 

Figure 7.7a and 7.7b is an example of the histogram and frequency distribution of 
bias factor XI and an example of resistant factor calibration for 50 cases of concrete 
piles in Clay using the a-Tomlinson method with correlation between the undrain 
shear strength Su and SPT value buy Terzaghi and Peck by using all data for 
cohesionless soil in Vietnam. The other histograms and frequency distribution of bias 
factor: XI toXS and resistant factor calibration: Ol to 08 corresponding to different 
methods for all data, north data, and south data are in the figure F-Cl-a to F-C8-d in 
appendix E 



137 



Lamdal AllClay data 

Normal 

Lognormal 




1.5 2 
Bias Factor 



Fig 7.7a Histogram and frequency distribution of bias factor X\ for 50 cases of 
concrete piles in Clay using the a-Tomlinson method (Su: Peck) in Vietnam 




2 3 

Reliability Index, p 



Fig7.7b Resistant factor calibration for 50 cases of concrete piles in Clay 
using the a-Tomlinson method (Su: Peck) in Vietnam 



138 



Table 7.2 Bias factor A, for driven pile in cohesive soil using a-Tomlinson, a- API method, X 
method, P-Burland, Shmertmann SPT method with Davission's criterion in North, Center and 
South of Vietnam 





Data from North, Central and South of Vietnam 


a-Tomlinson 
method 


a- API method 


X method 


B- 

Burland 


Schmertmann 
SPT 


Su- 
Terzaghi, 
Peck 


Su- 

Hara 


Su- 
Terzaghi, 
Peck 


Su- 
Hara 


Su- 
Terzaghi, 
Peck 


Su- 
Hara 


A,l 


12 


A,3 


14 


A,5 


16 


n 


A,8 


NP-Cl 


0.80 


0.40 


1.28 


0.62 


1.01 


0.49 


1.33 


0.75 


NP-C2 


1.03 


0.52 


1.64 


0.80 


1.30 


0.63 


1.71 


0.97 


NP-C3 


1.07 


0.56 


1.38 


0.77 


1.40 


0.76 


1.27 


0.92 


NP-C4 


0.98 


0.52 


1.27 


0.71 


1.28 


0.70 


1.16 


0.85 


NP-C5 


1.21 


0.64 


1.56 


0.87 


1.58 


0.86 


1.44 


1.05 


NP-C6 


1.26 


0.67 


1.63 


0.91 


1.65 


0.90 


1.50 


1.09 


NP-C7 


1.00 


0.53 


1.29 


0.72 


1.31 


0.71 


1.18 


0.86 


NP-C8 


1.09 


0.80 


1.35 


0.90 


1.48 


0.99 


1.07 


1.21 


NP-C9 


1.08 


0.79 


1.34 


0.89 


1.47 


0.98 


1.06 


1.20 


NP-CIO 


0.82 


0.60 


1.01 


0.68 


1.11 


0.74 


0.80 


0.91 


NP-Cll 


0.83 


0.61 


1.03 


0.69 


1.13 


0.75 


0.82 


0.92 


NP-C12 


0.79 


0.58 


0.98 


0.65 


1.07 


0.71 


0.77 


0.87 


NP-Cl 3 


0.85 


0.62 


1.05 


0.70 


1.15 


0.77 


0.83 


0.94 


NP-C14 


1.03 


0.77 


1.37 


0.77 


1.21 


0.64 


1.14 


0.93 


NP-Cl 5 


0.63 


0.47 


0.83 


0.47 


0.74 


0.39 


0.69 


0.57 


NP-Cl 6 


1.03 


0.77 


1.37 


0.78 


1.22 


0.64 


1.14 


0.93 


NP-Cl 7 


1.26 


0.85 


1.76 


0.81 


1.35 


0.66 


1.48 


0.97 


NP-Cl 8 


1.20 


0.81 


1.68 


0.77 


1.29 


0.63 


1.41 


0.93 


NP-Cl 9 


1.01 


0.71 


1.44 


0.69 


1.13 


0.56 


1.33 


0.82 


NP-C20 


0.89 


0.62 


1.27 


0.61 


1.00 


0.49 


1.17 


0.72 


NP-C21 


0.67 


0.50 


1.36 


0.42 


0.80 


0.44 


0.62 


0.63 


NP-C22 


1.03 


0.78 


2.10 


0.65 


1.23 


0.69 


0.96 


0.98 


NP-C23 


0.76 


0.74 


0.75 


0.66 


0.79 


0.72 


0.66 


1.06 


NM-C24 


1.47 


0.85 


2.17 


1.18 


1.58 


0.87 


1.68 


1.28 


NM-C25 


1.47 


0.85 


2.18 


1.18 


1.58 


0.87 


1.69 


1.28 


NM-C26 


1.65 


0.95 


2.43 


1.32 


1.76 


0.97 


1.88 


1.43 


NM-C27 


1 A f\ 

1.40 


A O 1 

0.81 


2.07 


1 1 O 

1.12 


1.50 


A O O 

0.83 


1.60 


1.22 


NM-C28 


1.10 


0.82 


1.73 


0.54 


0.86 


0.50 


0.85 


0.75 


NM-C29 


0.88 


0.66 


1.38 


0.43 


0.69 


0.40 


0.68 


0.60 


NM-C30 


0.87 


0.65 


1.37 


0.43 


0.68 


0.40 


0.68 


0.60 


NM-C31 


0.92 


0.69 


1.45 


0.46 


0.72 


0.42 


0.72 


0.63 


NM-C32 


0.90 


0.67 


1.41 


0.44 


0.70 


0.41 


0.70 


0.61 


NM-C33 


1.48 


0.94 


1.86 


1.13 


1.57 


0.91 


1.81 


0.88 


NM-C34 


0.46 


0.29 


0.58 


0.35 


0.49 


0.28 


0.56 


0.27 


NM-C35 


1.13 


0.71 


1.41 


0.86 


1.19 


0.69 


1.37 


0.67 


NM-C36 


1.18 


0.75 


1.48 


0.90 


1.25 


0.73 


1.44 


0.70 


NM-C37 


1.16 


0.73 


1.45 


0.89 


1.23 


0.71 


1.41 


0.69 


NM-C38 


1.11 


0.70 


1.39 


0.85 


1.17 


0.68 


1.35 


0.66 



139 



Table 1.2 (cont.) 



CP-Cl 


2A5 


1 O 1 

1.33 


1 O /I 

1.84 


1 1/1 

1.14 


1 /I 

1.64 


0.93 


1.20 


1 A'? 

1.07 


CP-C2 


2.65 


1 /I /I 

1.44 


1.99 


1.23 


1.77 


1 A 1 

1.01 


1 IT 

1.17 


1 1 

1.16 


CP-C3 


3.16 


1.71 


2.37 


1.46 


2.1 1 


1.20 


1.35 


1.38 


CP-C4 


2.40 


1.30 


1.80 


1.11 


1.60 


0.91 


1.10 


1.05 


CP-C5 


2.96 


1.61 


2.22 


1.37 


1.97 


1.12 


1.19 


1.29 




U.oZ 


U.OJ 


1 /I ^ 
1.4j 


U. / / 




U. / i 


U. / i 


c\ oo 


CP-C7 


1.35 


1.37 


2.38 


1.28 


2.28 


1.18 


1.18 


1.63 


CP-C8 


1.04 


1.05 


1.83 


0.98 


1.75 


0.90 


0.94 


1.25 


CP-C9 


1.29 


1.30 


2.27 


1.21 


2.17 


1.12 


1.13 


1.55 


CP-CIO 


1.16 


1.17 


2.04 


1.09 


1.95 


1.01 


1.04 


1.39 


SP-Cl 


1.51 


0.88 


1.68 


1.04 


1.80 


1.08 


1.44 


1.30 


SP-C2 


0.71 


0.68 


0.59 


0.43 


0.65 


0.43 


0.45 


1.08 



Table 7.2a Summary of calibration resistance factor for driven pile using a-Tomlinson, a- API 



method, ^ meth od, P-Burland, Shmertmann SPT method in North, Center and South of Vietnam 





Data from North, South and Central of Vietnam 


a-Tomlinson method 


a-API method 


A. method 


P- 

Burland 


Schmertmann 
SPT 


Su-T,P 


Su-H 


Su-T,P 


Su-H 


Su-T,P 


Su-H 


Total 


mean 


1.22 


0.81 


1.55 


0.83 


1.31 


0.74 


1.14 


0.97 


50 


stand 


0.57 


0.30 


0.46 


0.28 


0.42 


0.23 


0.35 


0.28 




GOV 


0.47 


0.37 


0.29 


0.34 


0.32 


0.31 


0.31 


0.29 


=2.33 


FOSM 


0.481 


0.391 


0.884 


0.435 


0.706 


0.411 


0.625 


0.554 


FORM 


0.498 


0.420 


0.975 


0.470 


0.775 


0.450 


0.680 


0.605 


Monte 


0.508 


0.417 


1.008 


0.478 


0.782 


0.455 


0.706 


0.599 


(p/A. 


0.42 


0.51 


0.65 


0.57 


0.60 


0.61 


0.62 


0.62 


FS 


2.7 


3.3 


1.4 


2.9 


1.8 


3.0 


1.9 


2.3 


FSx;^ 


3.3 


2.7 


2.1 


2.4 


2.3 


2.2 


2.2 


2.2 




FOSM 


0.345 


0.295 


0.694 


0.334 


0.547 


0.320 


0.487 


0.435 


FORM 


0.375 


0.325 


0.790 


0.378 


0.612 


0.365 


0.550 


0.490 


Monte 


0.373 


0.322 


0.836 


0.382 


0.630 


0.368 


0.571 


0.486 




0.31 


0.40 


0.54 


0.46 


0.48 


0.50 


0.50 


0.50 


FS 


3.7 


4.3 


1.6 


3.6 


2.2 


3.7 


2.4 


2.8 


FSx;^ 


4.5 


3.5 


2.6 


3.0 


2.9 


2.8 


2.7 


2.7 


Good result 




good 




good 




good 


good 


good 



1 Efficiency factor lEquivalent factor of safety to ASD 3 Actual mean factor of safety 4 Monte Carlo simulation 



140 



Table 7.2bSummary of calibration resistance factor for driven pile using a-Tomlinson, a-API 
method, X met hod, P-Burland, Shmertmann SPT method in North of Vietnam 





Data from North of Vietnam 


a-Tomlinson method 


a-API method 


A. method 


o 

P- 

Burland 


Schmertmann 

br 1 


Su-1 ,F 


C, , I 1 


Su- 1 ,r 


C I 1 


Su- 1 ,F 


C, , I 1 


Total 


mean 


1 r\ A 

1.U4 


U.68 


1.45 


U.75 


1 1 O 

1.18 


A /' n 

U.67 


1 1 zr 

1.16 


0.88 


38 


stand 


U.25 


r\ 1 /I 


U.4U 


U.zi 


0.32 


A 1 O 

U. lo 


A O O 

0.38 


A O /I 




cov 


U.24 


U.zl 


yj.Z 1 


U.3 1 


U.2 / 


f\ T7 
U.Z / 


0.3j 


yj.Z 1 


=2.33 


FOSM 


U.dj4 






M /I 1 O 


0. /04 




0.61 / 


U.JzL) 


FORM 


U./I5 


0.510 


f\ C\A /I 

0.946 


0.450 


0.115 


0.436 


0.6 /O 


A cn c 

0.5 /5 


Monte 


U./iU 


0.509 


0.940 


0.44o 


0.770 


0.434 


0.653 


0.57s 




U. /U 


U. / J 


U.DJ 


u.jy 


U.DO 


U.OJ 


0.56 


0.66 


FS 


2.1 


3.0 


1.6 


3.3 


2.0 


3.5 


z.z 


2.0 


FSxA, 


2.2 


2.1 


2.3 


2.5 


2.3 


2.3 


2.6 


2.3 


P=3 


FOSM 


0.526 


0.372 


0.681 


0.326 


0.559 


0.316 


0.476 


0.412 


FORM 


0.610 


0.435 


0.775 


0.370 


0.633 


0.362 


0.530 


0.475 


Monte 


0.610 


0.438 


Q.lll 


0.363 


0.634 


0.355 


0.521 


0.474 




0.59 


0.64 


0.54 


0.48 


0.54 


0.53 


0.45 


0.54 


FS 


2.6 


3.7 


2.0 


4.2 


2.5 


4.4 


2.9 


3.3 


FSx;^ 


2.7 


2.5 


2.9 


3.2 


2.9 


2.9 


3.3 


2.9 


Good result 


good 






good 


good 




good 


good 



Table 7.2c Summary of calibration resistance factor for driven pile using a-Tomlinson, a-API 
method, X met hod, P-Burland, Shmertmann SPT method in Central of Vietnam 





Data from Central of Vietnam 


a-Tomlinson method 


a-API method 


A method 


P 

Burland 


Schmertmann 
SPT 


Su-T,P 


Su-H 


Su-T,P 


Su-H 


Su-T,P 


Su-H 


Total 


avera 


1.93 


1.31 


2.02 


1.17 


1.86 


1.01 


1.10 


1.28 


11 


stand 


0.88 


0.26 


0.30 


0.20 


0.28 


0.15 


0.17 


0.21 




cov 


0.46 


0.19 


0.15 


0.17 


0.15 


0.15 


0.16 


0.17 


(3 

=2.33 


FOSM 


0.779 


0.901 


1.491 


0.834 


1.367 


0.743 


0.801 


0.916 


FORM 


0.830 


1.100 


1.750 


0.965 


1.590 


0.860 


0.925 


1.035 


Monte 


0.879 


1.023 


1.754 


0.966 


1.602 


0.872 


0.937 


1.030 


(p/A. 


0.46 


0.78 


0.87 


0.83 


0.86 


0.87 


0.85 


0.81 


FS 


1.8 


1.5 


0.9 


1.6 


1.0 


1.9 


1.7 


1.5 


FSxA, 


3.4 


2.0 


1.9 


1.9 


1.9 


1.9 


1.9 


1.9 


P=3 


FOSM 


0.563 


0.742 


1.250 


0.694 


1.145 


0.623 


0.669 


0.762 


FORM 


0.610 


0.880 


1.550 


0.840 


1.400 


0.750 


0.820 


0.920 


Monte 


0.650 


0.882 


1.557 


0.851 


1.422 


0.778 


0.825 


0.901 


(p/A 


0.34 


0.67 


0.77 


0.73 


0.76 


0.77 


0.75 


0.71 


FS 


2.4 


1.9 


1.1 


2.0 


1.2 


2.2 


2.1 


1.8 


FSxA 


4.7 


2.4 


2.2 


2.3 


2.2 


2.2 


2.3 


2.3 


Good result 




good 




good 




good 


good 


good 



141 



1.22 



North, Central and South of Vietnam 

■ phi ■ phi/lamda lamda 



1.55 



1.01 



0.81 



0.65 



1.31 



0.83 



0.78 
0.60 



1.14 



0.74 



0.71 



0.61* _0.62 
0.461 




0.97 



0.60 



0.62 



Figure 7.8a Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a- API method, X method, P-Burland, Shmertmann SPT 
method for Cohesive Soil in Vietnam with P =2.33 



North of Vietnam 



■ phi ■ phi/lamda ■lamda 

1.45 



1-18 1.16 




1 2 3 4 5 6 7 8 



Figure 7.8b Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a- API method, X method, P-Burland, Shmertmann SPT 
method for Cohesive Soil in North of Vietnam with P =2.33 



142 



Central of Vietnam 



1.93 



2.02 



I phi ■ phi/lamda ■ lamda 



1.75 



0.88 
jo.46 



i 



1.31 



0.87 



1.86 



1.60 



1.17 



0.86 



1.28 



1.10 

87 1.01 0.94 
0.87_ 0.85| 





Figure 7.8c Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
driven pile using a-Tomlinson, a- API method, X method, P-Burland, Shmertmann SPT 
method for Cohesive Soil in Central of Vietnam with P =2.33 

7.5.3 Resistant factors for driven piles in Mixed Soil 

Table 7.3, 7.3a, 7.3b, 7.3c, 7.3d shows the bias factor and the calibration 
resistance factor as well as efficiency factor {(p/X), equivalent factor of safety to 
ASD and actual mean factor of safety for driven pile in Mixed soil by different 
methods for calculating the nominal capacity in North, Central and South of 
Vietnam. The resistant factors by using FORM method and Monte Carlo 
simulation are almost the same and about 10% lower than FOSM method. Figure 
7.9a and 7.9b is an example of the histogram and frequency distribution of bias 
factor XI and an example of resistant factor calibration for 165 cases of concrete 
piles in mixed soil. The other histogram and frequency distribution of bias factor 
fromXl toA,15 and resistant factor calibration from Ol to 015 for different method 
and with all data, north data, and south data are in the figure F-Ml-a to F-M8-d in 
appendix F 



143 



y3 



CO. 

m "z. 



'£1 



y3 



o 
o 

ON 



p 
o 



o 



ON 
ON 



o 

3 
O 
[/I 

■a 
c 



11 



3 

GO 



NO 



OS 
NO 



p 

00 



NO 



ON 



O 



ON 

o 



p 

C/5 



o 



o 



NO 



ON 



ON 
ON 



3 

GO 



O; ON 



o 
o 



NO 



ON 



ON 
NO 



ON 



o 



NO 

o 



ON 



o 



ON 



NO 
NO 



id =j 

H ffl 



o 

•z. 
s 

o 



S3 

3 o 



NO 



E -a 



5 -2 



3 

GO 



^ o< 

(-< NO 



ON 



o 
o 



o 



ON 



NO 



P 
C/) 



p 

o 



ON 



3 

GO 



O; 
O 



ON 



o 



NO 

o 



2: 



144 



234.4 


183.0 


178.6 


174.3 


169.9 


165.6 


161.2 


305.9 


278.1 


250.3 


236.4 


222.5 


57.2 


58.8 


60.3 


61.8 


63.4 


64.9 


66.5 


45.2 


NO 
00 


93.2 


130.2 


134.0 


75.1 


83.4 


91.7 


77.5 


70.5 


37.1 


33.8 


30.4 


26.1 


28.8 


69.7 


73.3 


167.8 


370.2 


361.4 


352.6 


343.8 


334.9 


326.1 


1100.2 


1000.2 


900.2 


850.2 


800.1 


80.9 


83.1 


85.3 


87.5 


89.6 


91.8 


94.0 


63.1 


147.3 


147.3 


237.3 


243.3 


98.5 


109.5 


120.4 


198.4 


180.4 


32.6 


29.7 


26.7 


43.3 


47.9 


152.7 


160.7 


294.1 


388.3 


379.0 


369.8 


360.5 


351.3 


342.0 


1101.7 


1001.6 


901.4 


851.4 


801.3 


109.8 


112.7 


115.7 


118.7 


121.6 


124.6 


127.6 


77.5 


164.5 


150.1 


274.5 


270.8 


107.1 


119.0 


130.9 


198.4 


180.4 


43.7 


39.7 


35.7 


43.3 


47.9 


152.7 


160.7 


160.0 


362.7 


354.0 


345.4 


336.7 


328.1 


319.5 


1079.2 


981.1 


883.0 


833.9 


784.9 


84.6 


86.9 


ON 
00 


91.4 


93.7 


96.0 


98.3 


65.3 


136.5 


129.1 


242.2 


251.0 


98.4 


109.3 


120.2 


198.4 


180.4 


35.9 


32.6 


29.4 


43.3 


47.9 


152.7 


160.7 


282.4 


390.8 


381.5 


372.2 


362.9 


353.6 


344.3 


1118.4 


1016.7 


915.0 


864.2 


813.4 


97.2 


99.8 


102.4 


105.0 


107.7 


110.3 


112.9 


74.7 


161.1 


161.8 


268.1 


265.4 


105.9 


117.6 


129.4 


198.4 


180.4 


39.1 


35.5 


32.0 


43.3 


47.9 


152.7 


160.7 


157.3 


364.8 


356.1 


347.4 


338.7 


330.0 


321.4 


1090.9 


991.7 


892.6 


843.0 


793.4 


79.4 


81.6 


83.7 


85.9 


88.0 


90.2 


92.3 


64.8 


134.1 


134.8 


241.7 


250.1 


98.0 


00 
00 

o 


119.7 


198.4 


180.4 


34.4 


31.3 


28.2 


43.3 


47.9 


152.7 


160.7 


218.3 


424.7 


414.6 


404.4 


394.3 


384.2 


374.1 


1092.3 


993.0 


893.7 


844.1 


794.4 


107.4 


110.3 


113.2 


116.1 


119.0 


121.9 


124.8 


76.2 


205.7 


207.0 


298.5 


286.9 


103.9 


115.5 


127.0 


198.4 


180.4 


43.6 


39.6 


35.7 


43.3 


47.9 


152.7 


160.7 


222.5 


381.1 


372.0 


362.9 


353.9 


344.8 


335.7 


1096.1 


996.5 


896.8 


847.0 


797.2 


94.8 


97.3 


99.9 


102.4 


105.0 


107.6 


110.1 


73.8 


146.6 


147.6 


266.9 


268.5 


104.2 


115.7 


127.3 


198.4 


180.4 


39.8 


36.2 


32.6 


43.3 


47.9 


152.7 


160.7 


167.8 


320.0 


312.3 


304.7 


297.1 


289.5 


281.9 


689.6 


626.9 


564.2 


532.9 


501.5 


51.0 


52.4 


53.8 


55.2 


56.5 


57.9 


59.3 


44.7 


111.4 


119.7 


201.6 


186.1 


50.9 


56.5 


62.2 


150.6 


136.9 


34.7 


31.6 


28.4 


31.9 


35.3 


113.1 


119.1 


294.1 


338.0 


330.0 


321.9 


313.9 


305.8 


297.8 


691.2 


628.3 


565.5 


534.1 


502.7 


79.9 


82.0 


84.2 


86.4 


88.5 


90.7 


92.8 


59.1 


128.7 


122.5 


238.7 


213.6 


59.5 


66.1 


72.7 


150.6 


136.9 


45.8 


41.6 


37.4 


31.9 


35.3 


113.1 


119.1 


160.0 


312.4 


305.0 


297.5 


290.1 


282.7 


275.2 


668.6 


607.8 


547.0 


516.6 


486.3 


54.7 


56.2 


57.6 


59.1 


60.6 


62.1 


63.6 


46.9 


9 001 


101.5 


206.5 


193.9 


50.7 


56.3 


62.0 


150.6 


136.9 


38.0 


34.5 


31.1 


31.9 


35.3 


113.1 


119.1 


282.4 


340.5 


332.4 


324.3 


316.2 


308.1 


300.0 


707.8 


643.4 


579.1 


546.9 


514.7 


67.3 


69.1 


70.9 


72.7 


74.6 


76.4 


78.2 


56.4 


125.2 


134.2 


232.3 


208.2 


58.2 


64.7 


71.1 


150.6 


136.9 


41.2 


37.4 


33.7 


31.9 


35.3 


113.1 


119.1 


157.3 


314.5 


307.0 


299.6 


292.1 


284.6 


277.1 


680.3 


618.5 


556.6 


525.7 


494.8 


49.6 


50.9 


52.3 


53.6 


54.9 


56.3 


57.6 


46.5 


98.3 


107.2 


205.9 


192.9 


50.3 


55.9 


61.5 


150.6 


136.9 


36.5 


33.2 


29.9 


31.9 


35.3 


113.1 


119.1 


218.3 


374.4 


365.5 


356.6 


347.7 


338.8 


329.8 


681.7 


619.8 


557.8 


526.8 


495.8 


77.5 


79.6 


81.7 


83.8 


85.8 


87.9 


90.0 


79.1 


169.8 


179.4 


262.7 


229.8 


56.3 


62.5 


00 
00 
NO 


150.6 


136.9 


45.7 


41.5 


37.4 


31.9 


35.3 


113.1 


119.1 


222.5 


330.8 


323.0 


315.1 


307.2 


299.3 


291.5 


685.6 


623.2 


560.9 


529.7 


498.6 


64.9 


66.6 


68.4 


70.1 


71.9 


73.6 


75.4 


55.4 


110.8 


120.0 


231.2 


211.3 


56.5 


62.8 


69.1 


150.6 


136.9 


41.9 


38.1 


34.3 


31.9 


35.3 


113.1 


119.1 


M30 


M31 


M32 


M33 


M34 


M35 


M36 


M41 


M42 


M43 


M44 


M45 


M46 


M47 


M48 


M49 


M50 


M51 


M52 


M53 


M54 


M55 


M56 


M57 


M58 


M59 


M60 


M61 


M62 


M63 


M64 


M65 


M66 


M67 


M68 


M69 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 



145 



77.0 


92.4 


94.9 


97.3 


102.2 


178.3 


187.7 


197.0 


174.9 


58.0 


52.5 


63.6 


57.6 


55.2 


50.0 


68.5 


75.7 


28.6 


31.6 


63.3 


66.7 


70.0 


68.9 


72.5 


76.1 


44.9 


49.6 


178.0 


165.2 


61.1 


67.9 


74.7 


137.3 


135.3 


129.4 


226.1 


oo 

00 

so 


107.7 


110.6 


113.4 


119.1 


447.8 


471.3 


494.9 


138.6 


160.5 


145.2 


73.7 


66.7 


260.6 


235.8 


59.3 


65.5 


50.4 


55.7 


159.0 


167.4 


175.8 


103.5 


108.9 


114.3 


69.5 


76.9 


370.6 


336.3 


53.3 


59.2 


65.1 


394.9 


399.9 


427.3 


174.2 


00 
00 
so 


104.8 


107.6 


110.3 


115.8 


376.9 


396.7 


416.6 


138.6 


168.3 


152.3 


101.4 


91.8 


260.1 


235.3 


75.3 


83.3 


50.4 


55.7 


140.4 


147.8 


155.2 


142.4 


149.9 


157.4 


86.6 


95.8 


266.1 


244.0 


67.9 


75.5 


83.0 


349.3 


352.1 


379.1 


174.2 


168.8 


64.8 


66.5 


68.2 


71.6 


319.7 


336.5 


353.3 


138.6 


147.2 


133.1 


82.7 


74.9 


252.3 


228.3 


57.2 


63.2 


50.4 


55.7 


121.9 


m 

00 
(N 


134.8 


113.7 


119.6 


125.6 


73.1 


oo 
d 

00 


174.4 


159.2 


47.8 


53.1 


58.4 


322.3 


326.6 


353.2 


192.3 


168.8 


152.7 


156.7 


160.7 


168.8 


427.7 


450.2 


472.7 


138.6 


175.7 


159.0 


88.3 


79.9 


264.2 


239.1 


72.4 


80.0 


50.4 


55.7 


160.4 


168.9 


177.3 


122.1 


128.5 


134.9 


00 


89.6 


317.7 


292.4 


67.4 


74.9 


82.4 


373.9 


376.4 


404.1 


192.3 


00 
00 

so 


84.9 


87.1 


89.4 


93.8 


350.9 


369.4 


387.9 


138.6 


155.0 


140.2 


76.6 


69.3 


255.6 


231.3 


54.5 


60.2 


50.4 


55.7 


131.1 


138.0 


144.9 


104.9 


110.4 


115.9 


71.2 


78.7 


219.3 


200.8 


47.2 


52.5 


57.7 


335.8 


339.8 


367.4 


174.2 


00 
00 
so 


183.0 


187.8 


192.6 


202.2 


351.2 


369.7 


388.2 


138.6 


152.0 


137.5 


86.5 


78.3 


260.4 


235.6 


83.1 


91.9 


52.5 


58.0 


138.8 


146.1 


153.4 


119.8 


126.1 


132.4 


96.2 


106.4 


504.3 


466.3 


53.2 


59.1 


65.0 


364.1 


361.7 


387.9 


192.3 


00 
00 
so 


114.5 


117.5 


120.5 


126.6 


363.3 


382.4 


401.5 


138.6 


142.4 


128.8 


85.4 


77.3 


257.0 


232.5 


67.1 


74.1 


50.4 


55.7 


129.8 


136.6 


143.4 


123.9 


130.4 


136.9 


79.6 


87.9 


207.5 


191.9 


48.3 


53.7 


59.0 


331.3 


333.5 


361.4 


174.2 


125.0 


111.0 


113.9 


116.9 


122.7 


384.8 


405.0 


425.3 


145.7 


96.2 


87.1 


40.5 


36.6 


94.0 


85.1 


61.3 


67.7 


25.7 


28.4 


127.7 


134.4 


141.2 


48.9 


51.5 


54.1 


42.7 


47.2 


377.7 


343.3 


00 


53.4 


58.7 


311.0 


289.3 


318.4 


169.2 


125.0 


113.1 


116.1 


119.0 


125.0 


313.9 


330.4 


347.0 


232.5 


104.1 


94.2 


68.2 


61.7 


93.5 


84.6 


77.4 


85.5 


25.7 


28.4 


109.1 


114.8 


120.6 


87.9 


92.5 


97.1 


59.8 


66.1 


285.2 


263.0 


67.9 


75.5 


83.0 


265.4 


241.5 


270.2 


254.1 


125.0 


00 
so 


69.8 


71.6 


75.2 


256.7 


270.2 


283.7 


168.6 


82.9 


75.0 


49.5 


44.8 


85.8 


77.6 


59.2 


65.4 


25.7 


28.4 


90.6 


95.4 


100.1 


59.1 


62.2 


65.3 


46.2 


51.1 


181.5 


166.2 


42.6 


47.3 


52.0 


238.4 


216.0 


244.3 


159.2 


125.0 


88.2 


90.6 


92.9 


97.5 


364.7 


383.9 


403.1 


218.3 


111.5 


100.9 


55.1 


49.8 


97.6 


88.3 


74.4 


82.2 


25.7 


28.4 


129.1 


135.9 


142.7 


67.5 


71.1 


74.7 


54.2 


59.9 


336.7 


311.4 


42.0 


46.7 


51.3 


290.0 


265.8 


295.2 


242.7 


125.0 


88.2 


90.5 


92.8 


97.4 


287.9 


303.1 


318.2 


162.1 


90.7 


82.1 


43.4 


39.3 


89.0 


80.5 


56.5 


62.4 


25.7 


28.4 


99.7 


105.0 


110.2 


50.3 


53.0 


55.6 


44.3 


49.0 


226.3 


207.9 


42.0 


46.7 


51.3 


251.9 


229.2 


258.5 


154.4 


125.0 


191.3 


196.3 


201.3 


211.4 


288.2 


303.4 


318.6 


221.3 


87.8 


79.4 


53.3 


48.2 


93.8 


00 
00 


85.2 


94.1 


27.8 


30.7 


107.5 


113.1 


00 
00 


65.3 


68.7 


72.1 


69.4 


76.7 


523.3 


485.3 


47.9 


53.3 


58.6 


280.3 


251.1 


278.9 


225.2 


125.0 


117.8 


120.9 


124.0 


130.2 


300.3 


316.1 


331.9 


133.5 


78.2 


70.7 


52.2 


47.2 


90.4 


81.8 


69.1 


76.4 


25.7 


28.4 


98.5 


103.6 


108.8 


69.3 


73.0 


76.6 


52.7 


58.2 


214.6 


198.9 


43.1 


47.9 


52.6 


247.4 


222.9 


252.5 


170.8 


M70 


M71 


M72 


M73 


M74 


M75 


M76 


M77 


-M78 


M81 


M82 


M83 


M84 


M85 


M86 


M87 


M88 


M89 


M90 


M91 


M92 


M93 


M94 


M95 


M96 


M97 


00 
OS 


M99 


M102 


M103 


M104 


M105 


M106 


M107 


SOIIAI 


-Ml 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NM 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


CP 



146 



o 


ON 


NO 


m 






1^ 




00 


ON 


(N 


00 




(N 


(N 




tN 


NO 


ON 


Cn] 


NO 


ON 




NO 


p 


rn 




p 






c^ 








in 


in 


00 

m 

(N 


o^ 


rn 

NO 
<N 


ON 

<N 


d 
m 


o 


d 
m 
m 


NO 

m 


iri 

00 


rn 

ON 

CNl 


O 


iri 

00 

m 


NO 

m 


o 


o 


d 
m 
m 


ON 


iri 

00 

fNl 


ON 

(N 


00 
ON 

(N 


o 
m 


d 

c^ 


c^ 


C^ 

CN 
c^ 


d 

c^ 


NO 

c^ 


CN 


ON 


iri 
in 


NO 
C^ 


ic^ 

ION 


00 
ON 


o 


c-n 
o 


in 
o 


o 


Tt; 




(N 


(N 




NO 


in 


in 


NO 




NO 


NO 


in 


NO 


NO 


in 


O 


1^ 


m 


O 


NO 


CN 


ON 


iri 




°° 






t-~; 


C^ 


ON 


C^ 


c — 


c^ 


ON 


in 


00 


ON 


ON 
ON 


O 
(N 
CnI 


IT) 


00 

o 
m 


(N 

in 
CN 


d 
oo 
CN 


ON 
(N 


(N 

rNi 


00 

o 
m 


ON 

rNi 


d 

00 

rNi 


00 

o 
m 


00 

o 
m 


rj 
in 
rNi 


ON 

rNi 


00 
ON 

CN 


iri 
o 
m 


CN 

m 


00 

m 


iri 
CN 


C^ 


o6 


iri 


in 


oo 
in 


iri 

NO 


1^ 


oo 
c^ 


^' 




ON 


00 


CN 

00 


-*' 

00 




NO 


fN 






NO 






NO 




NO 


NO 




NO 


NO 




o^ 


"ri 




t — 




ON 


"ri 




GO 




p 


NO 


tN 


00 


CON 




tN 


c^ 




<ri 


00 


(N 

ON 


ON 
ON 


d 

(N 


(N 
iri 
(N 


00 

o 
m 


(N 
in 

(N 


d 

00 
(N 


ON 
(N 


(N 


00 

o 
m 


ON 
(N 


d 

00 


00 

o 


00 

o 


(N 

in 

(N 


NO 
(N 


(N 
iri 
tN 


00 

iri 
tN 


NO 

tN 


ON 
NO 

tN 


CN 


d 

00 
CN 


NO 
00 
CN 


ON 

CN 


t-^ 

ON 

CN 


c^ 
O 
c^ 


0(3 
O 
c^ 


c^ 


CON 
C^ 


OC 
ON 


CN 

o 


in 
o 


1^ 
o 


ON 

o 






NO 






r*^ 










CN 


















"Nt" 




r*^ 


r*^ 


r*^ 


tN 


tN 


tN 








O 


in 


00 




NO 


CN 




s 


(N 
CN 


<N 
<N 




ON 




ON 


d 
m 


iri 
m 


oo' 


m 


in 

(N 

m 


d 






ON 

rNi 


rj 

NO 

tN 


00 
NO 
tN 


tN 


d 

00 
tN 


NO 
00 
tN 


tN 
ON 
CN 


od 

ON 
CN 


^' 
O 
c^ 


d 

c^ 


NO 

m 


tN 
tN 


oo 

tN 




d 


CN 
c — 


c — 


1^ 
c — 


00 

c — 


O 
GO 


GO 


Tt- 






IT) 


rn 


rn 


rn 




oo 


fN 


m 


00 


m 






m 




ON 


00 


NO 


in 




tN 


O 


00 




in 


^ 


tN 




°° 


CON 


p 






tN 


o 

(N 


(N 
(N 


CN 
(N 
(N 


>ri 
(N 


ON 

(N 


m 


ON 

(N 


d 
m 


iri 
(N 
m 


00 


m 


iri 
(N 
m 


d 
m 


m 


m 


ON 

(N 


iri 
m 


in 


d 

NO 

m 


00 
NO 

m 


NO 

m 


^' 

00 
c^ 


tN 

On 
c^ 


d 
o 


o 


iri 


CN 


rn 


C3N 




no' 

ON 


CON 
ON 


c^ 

o 


iri 
o 


o 


ON 

o 


■nI" 


NO 


CN 




i/^ 


NO 






NO 




NO 


NO 




NO 


NO 






00 


iri 




00 






00 






00 






r — 




t — 




CN 


00 




00 


(N 

ON 


ON 
ON 


d 

<N 


(N 
<N 


00 

o 
m 


(N 
in 

CNl 


d 

00 

CNl 


ON 

CNl 


CNl 


00 

o 
m 


ON 

CNl 


d 

00 

CNl 


00 

o 
m 


00 

o 
m 


in 

CNl 


ON 

CNl 


in 


d 

NO 


NO 
NO 
<N 




CN 


rn 
00 
CN 


o6 

00 
CN 


On 
CN 


d 
o 
m 


iri 
o 

c^ 


c^ 


c^ 


CN 
CN 
c^ 


CN 
t — 


NO 
t — 


00 
t — 


CON 
t — 


c^ 
00 




NO 




IT) 




m 


m 


m 


00 




rn 


00 


rn 


rn 


rn 


rn 


NO 


ON 








irj 


°° 


CN 


NO 


p 


c^ 






in 






CN 




CN 






(N 


(N 


(N 


ON 
(N 


m 


ON 

(N 


d 
m 


in 
m 


oo' 


m 


in 
m 


d 
m 






ON 

(N 


(N 






d 


d 


Os 


0C3 


0C3 






NO 

»n 


iri 
in 


iri 
in 


in 






in 


tN 


d 


pi 




NO 


(N 


(N 


in 


NO 


in 


in 


NO 




NO 


NO 


in 


NO 


NO 


in 


(N 


p 


00 


NO 




CN 


O 


0C3 


NO 




tN 


O 


00 


NO 


ON 


NO 


^. 


tN 


p 


(ON 


rn 

00 


ON 


ON 
ON 


d 


(N 

in 

(N 


00 

o 
m 


(N 

in 

CNl 


d 

00 
CnI 


^' 

ON 
tN 


^' 
tN 


00 

o 


^' 

ON 

CN 


d 
oo 
CN 


00 

O 

fO 


00 

o 
m 


(N 

m 

fN 


ON 
ON 
tN 


NO 

o 
m 


(N 

m 


ON 

m 


NO 
(N 


rn 
m 


d 


NO 


rn 
in 
c^ 


d 

NO 
C^ 


t-^ 

NO 
C^ 




d 
oo 
c^ 


OO 
c^ 


irl 

00 


00 
00 


ON 


rn 

CON 


iri 

ON 


NO 
(ON 






NO 




ON 




ON 


CN 


00 






00 


CN 


ly-j 




ON 






00 


iri 


tN 


ON 


NO 


tN 


ON 


NO 












oc: 


in 


c^ 




CON 


00 


00 


rn 
On 




rn 

NO 
<N 


rj 

(N 

m 


r<i 

NO 


r<i 

ON 
CN 


o 
m 


m 


rj 

(N 

m 


o 
m 


r<i 

ON 
CN 


(N 
(N 

m 


(N 
(N 

m 


rn 

NO 


d 
in 


NO 

in 


NO 


NO 
<N 


rn 
<N 


0<D 
CN 


00 
CN 


d 

On 
CN 


iri 

On 
CN 


o 

rn 


o 


rn 


0<D 

rn 


CN 

rn 


00 


NO 
00 


ON 
00 


ON 


c-n 

ON 


ON 




00 


NO 


rn 


p 


(N 


p 






ON 


(N 






(N 


(N 


p 


p 


p 


p 










CN 


CN 


CN 


CN 


c^ 


c^ 


c^ 




NO 


p 


c-n 


NO 


CON 


CN 


o 
oo 


ON 


(N 

fNl 


o^ 


rn 

NO 


ON 
1^ 




(N 

"Nf 


NO 

rn 


rn 

NO 


(N 




rn 

NO 


rn 

NO 


ON 

Pi 


ON 

o 


NO 


rn 
rn 


d 

rn 


t-^ 
rn 




IT) 


OO 
IT) 


iri 

NO 


CN 
rn 


ON 

rn 


NO 
X 


c^ 

ON 


d 
o 


oo 
o 




iri 


t-^ 


CON 


CN 


y3 


p 


^ 


NO 


NO 




NO 


p 




(N 






o 






NO 


ON 


0\ 


ON 


OS 


OS 


Os 


P 


P 


P 


p 


p 












CO^ 








VO 


NO 


00 


O 

Cn) 


Cn) 


d 

ON 


m 


NO 
CN 






d 

ON 
CN 




NO 

CN 


d 

ON 
CN 


d 

ON 


m 


d 

tN 


iri 
<N 
tN 


d 
m 

tN 


iri 
m 

tN 


d 

tN 


iri 
tN 


iri 
tN 


NO 

iri 
tN 


NO 

tN 


NO 
NO 

tN 


tN 


NO 

1^ 

tN 


00 

tN 


NO 
00 
tN 


00 


-*' 

00 


NO 
00 


0(3 
00 


d 

CON 


CN 

CON 






00 








1^ 


ON 


o 


in 




o 


ON 








in 




m 


(N 


O 


ON 


00 




NO 


in 


^ 


c^ 


CN 




o 




00 




C^ 


NO 


>ri 

IT) 


00 
NO 
(N 


00 


00 

o 
m 


NO 

m 




NO 

m 


o 




CNl 

m 




(N 
CNl 
'S- 


o 




(N 


NO 

m 


m 
o 
m 


O 

m 


m 


fNl 

m 


m 
m 


C^ 


c^ 


iri 
c^ 


00 

iri 
c^ 


iri 

NO 
C^ 


CN 
1^ 
c^ 


ON 
1^ 
C^ 


NO 
00 
C^ 


ON 

rn 


NO 

o 


CON 

o 


CN 


in 




CON 


^ 


t-^ 


p 


NO 


t-^ 




t-^ 






ON 


(N 


m 






(N 


t-^ 


in 


(N 


ON 








°° 


in 


CN 


ON 




^ 




°° 


c^ 


ON 


in 


c^ 


p 






O 
1^ 


1^ 


iri 

ON 


m 

(N 


rn 
00 
(N 


m 


t-^ 
in 


d 

(N 


iri 
o 

(N 


rn 
00 
(N 


d 

(N 


in 


rn 
00 
(N 


rn 
00 
(N 


m 


o 

(N 




NO 

(N 


CN 
(N 


NO 

CN 
CN 


CN 


iri 

m 

CN 


d 

CN 


iri 
CN 


ON 

CN 


iri 
CN 


ON 

iri 
CN 


^ 
NO 

tN 


00 
NO 

CN 


00 


c^ 

00 


NO 
00 


0(3 
00 


d 

ON 


ON 


o 


O^ 




"Nf 




NO 




p 




00 


NO 




p 


NO 


NO 




O^ 


"Nf 


GO 


tN 


t — 




"ri 


O^ 




GO 


tN 


t — 




<ri 


ON 


CO^ 


p 








rn 


00 


O^ 
(N 


NO 
00 


O^ 


o 


ON 
PJ 


NO 
NO 


00 


(N 

ON 


(N 
O 


00 


NO 
NO 


(N 
O 


(N 
O 


ON 


d 


ON 
p- 


oo 


NO 
ON 


O 


c^ 




ON 


OO 


NO 


iri 


c^ 


CN 


d 


NO 
CN 


d 

c^ 


in 
c^ 


c^ 


d 


C^ 


1^ 




m 


ON 




NO 


'd- 


o 


00 


00 


NO 


00 


o 


NO 


NO 




NO 


^ 


m 




p 


00 


1^ 


NO 




rn 




O 


00 






CN 


CN 


CN 


CN 


C^ 


ON 


00 
00 


iri 

ON 


iri 

(N 


00 


rn 

o 
m 


00 

CNl 


NO 

CNl 


ON 
00 

CNl 


d 

(N 

CNl 


o 


ON 
00 

CNl 


NO 

CNl 


o 
m 


rn 

o 
m 


00 

CNl 


in 

CNl 


rn 

NO 
<N 


oi 

NO 
<N 


iri 
<N 


00 
CN 


NO 
00 
CN 


CN 
On 
CN 


OO 
On 
CN 


o 


d 


NO 


CN 
CN 


CN 


c^ 
c^ 
c^ 


iri 

CON 


00 
ON 


O 


c^ 
O 


in 
o 


O 








IT) 


NO 




00 


ON 


o 




% 


m 
% 




in 
% 


NO 


% 


o 

tN 




fNl 
fNl 


m 


CN 


iri 
CN 


NO 

CN 


1^ 
CN 


00 
CN 


On 
CN 


o 

rn 


rn 


CN 
rn 


rn 
rn 


c-n 


in 
c-n 


NO 

c-n 


1^ 

c-n 


00 
c^ 


CON 
c^ 


u 


o 


fi 

U 


fi 

o 


u 


u 


U 


u 


U 


u 


u 


u 


u 


u 


u 


U 


u 


u 


u 


u 


u 


u 


u 


u 


u 


u 


d 

u 


U 


d 

u 


u 


u 


u 


u 


u 


u 


u 



147 



72.3 


76.3 


80.3 


88.3 


102.8 


105.0 


107.2 


109.5 


111.7 


113.9 


116.2 


118.4 


120.7 


75.4 


77.0 


78.6 


81.8 


85.0 


348.3 


385.0 


73.8 


77.9 


82.0 


90.2 


165.0 




189.5 


°°. 

00 


89.0 


173.2 


83.4 


88.0 


92.6 


101.9 


296.2 


302.7 


309.1 


315.5 


322.0 


328.4 


334.9 


341.3 


347.7 


58.9 


60.1 


61.4 


63.9 


66.4 


871.9 


963.7 


87.3 


92.2 


97.0 


106.7 


377.0 


392.4 


201.5 


453.7 


378.8 


501.8 


(N 


00 




<n 


(N 






in 


o 




ON 


m 




rn 




in 


NO 






On 




00 


m 


(N 


NO 


ON 


in 


ON 


0(3 


m 


O 

o 


in 
o 




(N 

CnI 


NO 
ON 
(N 


(N 
O 

m 


ON 

o 
m 


iri 
m 


(N 
!N 

m 


od 

!N 

m 


m 
m 


m 


m 


ON 


ON 
ON 


o 


iri 
o 


ON 

o 


00 

in 


m 

00 


NO 


(N 


ON 
CnI 




NO 

m 


od 
1^ 
m 


m 

CN 


mi 
m 


NO 

m 


NO 
00 


62.5 


66.0 


69.4 


76.4 


296.2 


302.7 


309.1 


315.5 


322.0 


328.4 


334.9 


341.3 


347.7 


66.6 


68.0 


69.5 


72.3 


75.1 


671.3 


741.9 


94.2 


99.4 


104.7 


115.1 


340.7 


362.4 


175.5 


451.5 


365.2 


465.9 


o 


oo 


NO 










«n 


q 


^, 


ON 






00 


NO 




q 


NO 








ON 


NO 


CN 


oo 


(n 


CNj 


a\ 


oo 


ON 


o 


ON 

o 


>n 


(N 


NO 
ON 

(N 


rj 
o 
m 


ON 

o 
m 


in 

m 


(N 
(N 

m 


od 

(N 

m 


m 
m 


m 


m 


00 


NO 
00 


od 

00 


(N 

ON 


iri 

ON 


00 


ON 

(N 

ON 


o 


ON 

o 


mi 


CN 


mi 

00 

m 


rn 
m 


NO 
CN 


m 


mi 

00 

m 


CN 
O 

in 


67.0 


70.7 


74.4 


81.9 


296.2 


302.7 


309.1 


315.5 


322.0 


328.4 


334.9 


341.3 


347.7 


62.0 


63.4 


64.7 


67.3 


70.0 


732.4 


809.5 


89.2 


94.2 


99.2 


109.1 


354.3 


371.7 


178.9 


453.2 


371.8 


482.1 




(N 




NO 


(N 






in 


q 




ON 


rn 




CNl 


00 




NO 


ON 


NO 


(N 


ON 


NO 


(N 






CN 




q 




o 


od 

<N 


iri 
m 




NO 

>n 


NO 
ON 

(N 


(N 
O 

m 


ON 

o 
m 


in 
m 


(N 

CnI 

m 


od 
m 


m 
m 


m 


m 


NO 
1^ 




ON 


(N 

00 


in 

00 


(N 

in 

NO 


CN 


NO 

m 




(N 

m 


NO 


NO 

m 


d 
m 


oi 

00 


mi 

NO 


oi 

NO 

m 


ON 


78.7 


83.0 


87.4 


96.1 


296.2 


302.7 


309.1 


315.5 


322.0 


328.4 


334.9 


341.3 


347.7 


66.9 


68.3 


69.7 


72.6 


75.4 


653.9 


722.8 


104.0 


109.8 


115.5 


127.1 


343.0 


368.5 


166.1 


454.9 


369.0 


482.1 


78.4 


82.7 


87.1 


95.8 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


54.1 


55.3 


56.4 


58.7 


61.0 


788.2 


871.2 


61.6 


65.0 


68.5 


75.3 


266.6 


295.2 


189.5 


291.8 


272.5 


369.0 


(N 


<n 


00 




<n 




t-^ 


rn 


ON 


in 






rn 


NO 


in 


in 








rn 








00 


CN 






q 


NO 


in 


iri 

ON 


d 
o 


in 
o 


NO 


iri 

NO 


ON 
NO 


IN 
1^ 


NO 


ON 
1^ 


rn 

00 


00 


d 

ON 


ON 


ON 


ON 


NO 
ON 


d 
o 


o 


NO 


iri 


d 

On 


mi 

On 


d 
o 


d 


m 

CN 


00 
CN 


o^ 

CN 


On 
CN 


d 

CN 


rn 
in 
m 


57.5 


60.7 


63.9 


70.3 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


61.9 


63.2 


64.5 


67.1 


69.8 


587.6 


649.4 


68.5 


72.3 


76.1 


83.7 


230.3 


265.2 


163.4 


289.6 


258.9 


333.2 


99.0 


104.5 


110.0 


121.0 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


80.0 


81.7 


83.4 


00 
NO 
00 


90.2 


757.4 


837.2 


78.4 


82.7 


87.1 


95.8 


275.4 


296.3 


249.1 


296.1 


279.5 


370.1 


62.0 


65.4 


68.9 


75.8 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


57.3 


58.5 


59.7 


62.2 


64.6 


648.7 


717.0 


63.5 


67.1 


70.6 


77.7 


243.9 


274.5 


166.9 


291.4 


265.5 


349.4 




q 


00 


in 


in 




t-^ 


rn 


ON 


in 






m 




ON 




in 


in 


ON 




(N 


^ 


NO 


q 


q 


q 








CN 


rn 
(N 


d 
m 


NO 

m 


d 
in 


in 

NO 


ON 
NO 


(N 


NO 

1^ 


ON 
1^ 


rn 
00 


00 


d 

ON 


ON 


1^ 








d 

00 


od 

NO 

in 


od 

CnI 
NO 






rn 
CnI 


NO 

m 


NO 
NO 

CN 


rn 
1^ 

CN 


t-^ 
1^ 


m 
o 
m 


m 

NO 

CN 


NO 

m 


73.7 


77.7 


81.8 


90.0 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


62.1 


63.4 


64.8 


67.4 


70.1 


570.2 


630.3 


78.3 


82.6 


87.0 


95.7 


232.5 


271.3 


134.4 


293.1 


262.7 


349.4 


CP-M40 


CP-M41 


CP-M42 


CP-M43 


SP-Ml 


SP-M2 


SP-M3 


SP-M4 


SP-M5 


SP-M6 


SP-M7 


SP-M8 


SP-M9 


SP-MIO 


SP-Mll 


SP-M12 


SP-M14 


SP-Ml 6 


SP-Ml 7 


SP-Ml 8 


SP-Ml 9 


SP-M20 


SP-M21 


SP-M22 


SP-M23 


SP-M24 


SP-M25 


SP-M26 


SP-M27 


SP-M28 



148 



T 




Bias Factor 

Fig 7.9a Histogram and frequency distribution of bias factor 12 for 165cases of concrete piles in 
Mixed soils using the a-Tomlinson and Nordlund/Thurman method (Su: Hara, (|): P) in Vietnam 



1 




Q "I I \ I \ I \ \ \ \ \ ^ 

-0.5 0.5 1 1.5 2 2.5 3 3.5 4 

Reliability Index, (3 

Fig 7.9bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the a- 
Tomlinson and Nordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thombum) in 
Vietnam 



149 



a 

> 

o 



3 ■ 
O 
CO 

t; 

O 

s 

o 



3 

t 
O 

-a 
H 

o 

^' 
o 

s 

p 



e 



O fin 

00 CO 



_ 1^ >i 3 
m ^ ^ 



o 



3 



O 



=5 
O 



H 2 H 



GO 



GO ^ 



GO ^ 



GO ^ 



GO 



GO 



■a ^ a 
m ^ ^ 



3 



J, 

c« cj b 

C 3 g 

5 I ^ 

H ^ H 



GO ^ 



GO ^ 



1 Ph 
GO ^ 



5 S 

GO 



GO ^ 



O 



On 
O 



CM 



o 



CM 



On 
CO 

o 



O 



CM 



m 
o 



CO 



yr, 



On 
m 



o 



(N 



o 



CO 



o 
CO 

o 



(N 



O 



ON 

CO 
o 



CO 



IT) 

o 



CM 



O 



O 



O 



ON 



o 



oo 



On 



CO 



O 
in 



in 
o 



in 
o 



O 



o 



O 



CO 

CO 



m 
o 



o 



1^ 
in 



o 



in 



rH 
O 



O 



O 

in 



ON 

m 



yr, 



o 
in 



00 
O 

Ph 



O 



-H 1) 



CO 

CO 
■ (N 

II 



GO 

o 

Ph 



O 



o 
o 

■ r<-i 

II 



150 



a 

o 

GO 



O 

e 



B 

> 
O 

-a 

V. 
o 



=3 § d 

m ^ H 



■73 
3 



3 



O 



=5 J, 



1li 

H ^ H 



oo 



C/3 [-H 



oo 



oo ^ 



oo ^ 



O 



CM 



oo 



OS 



in 
o 



ON 

o 
m 



o 
o 



o 
cn 

o 



in 
o 



oo 



in 
o 



in 



o 



in 



(N 
CO 



O 



m 



in 
CO 



ON 

© 



oo 
in 



(N 



o 

O 



in 
m 



o 



oo 
CO 



O 
O 



o 



o 



o 



oo 
(N 
cn 
o 



in 



On 



O 



O 



O 

Q 



(Si 5 



'si- 

'si- 



m 

m 
o 



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in 



3 

t 
O 

H 

C3 
O 



o 



o 

e 



3 



5 3 



■73 
3 



° "3 d 

!/: cd H 

C 3 g 

H ^ H 



oo 



o 
o 



o 

oo 

o 



o 

On 

CO 



in 
o 



i 

GO 



fin 



1^ 

m 
in 



SO 

m 
o 



00 



GO ^ 



ON 

m 



ao 



oo 
o 



I 

00 



in 



o 



ON 

m 



3 
00 



o 
o 



o 



On 
O 



1^ 



oo f-H 



m 
o 



oo 



in 
o 



3 3 



oo 
O 



o 



43 

"C On „ 
2^ O 



9- 



C2. 



II 



00 
O 



o 



&■ 1 



C2. 



O 
O 

■ CO 

II 



o 
o 

a 



151 



a 

-4— » 

> 
o 

O ■ 



o 
Q 



m ^ H 



O 



s- 

O 
GO 



O 

e 



3 



C5 O 



5^ 



a 

o 



3 



00 



i 



fin 



-5 !-H -3 

m z H 



3 

O 
41 

H 

O 



3 



O 



o 

fin 



o 

^ ■ 
e 



a 

o 



H 

I 

GO 



GO 



00 



3 

GO 



00 



oo 



On 
m 



GO 



oo 
oo 



o 
>r, 
o 



o 



o 



o 



OO 



ON 



oo 



m 
oo 



o 



(N 



oo 
CO 
o 



in 
o 



On 



o 

On 

CO 



in 



in 
in 



On 
O 



O 



O 

in 



o 
en 



ON 

o 



in 
o 



o 



00 

o 



o 
o 



o 



m 
m 



o 



o 

IT) 



o 
in 



o 



ON 

in 



CO 



O 
CO 



oo 



oo 
(N 



o 

(N 

1^ 



On 



in 



as 

00 

o 



in 



o 
o 



oo 
m 
m 



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o 



o 

oo 



oo 



o 



in 



in 



o 



o 



in 



00 



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in 
o 



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in 



id o 



T3 



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CO 
CO 
(N 

II 

02. 



~9- 



GO 

o 



o 



&■ 1 



O 

o 
■ d 

II 



152 



^ 3 

Id O 



B 

v. 

a 

a 

a 

o 

e 



a 
a 
> 

o 

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O 

a 

o 

-I— » 

Q 



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O 

H 
o 

o 

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a 

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03 



3 



3 



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.all 
I =a I 

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GO H 



GO 



GO H 



GO 



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CO. 



§ — 



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m 2 H 



3 



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"a 3 



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GO 



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GO 



GO H 



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GO H 



ON 



o 
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o 



1^ 
in 

CM 



CO 



1^ 
oo 



m 
o 



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o 



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153 



q 


















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1/3 

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00 

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(1> 
> 



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(1> 
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o 



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a> 

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g (i> 




155 



7.5.4 Statistical sample size requirements for calibration the resistance factor 
for driven piles in Vietnam 

To calibrate the resistance factor for driven piles requires collecting a certain number of 
the static load tests and soil profiles data. To find out how many data are needed for 
calibration the resistance factor, a number of bias factor data sets from 5 data to 100 data 
with increment of one data was randomly picked up 100 times from 165 data for driven 
piles in mixed soil and each time pick up the resistance factors was calibrated by using 
Monte-Carlo simulation method and mean value for each set of data was calculated. 
Figure 7.12, 7.13, 7.14, 7.15 and 7.16 show the number of data sets versus the resistance 
factor for driven piles in mixed soil using different methods. From the result, number of 
data is need for calibration for resistance factor is 40 data for driven piles since the 
number of data more than 40 data the resistance factor calculated is almost the same. 

0.54 

0.52 

Q 0.5 
o 

CO 

LU 
Q) 

o 0.48 
c 



0.44 
0.42 

10 20 30 40 50 60 70 80 90 100 

Number of data 

Fig 7.12 Number of data versus the resistance factor O with Pt =3.0 for driven piles in 
mixed soil from North, Central and South of Vietnam using a-Tomlinson & Nordlund- 
Thurman method ( Su from Terzaghi and Peck and cD from Peck, Hanson and 
Thornbum) 



156 




0.48 




0.36 I ' ' ' ' ' ' ' ' ' 1 

10 20 30 40 50 60 70 80 90 100 



Fig 7.13 Number of data versus the resistance factor (I>with Pt =3.0 for driven piles in 
mixed soil from North, Central and South of Vietnam using p Burland & Northlund- 
Thurman method ( O from Peck, Hanson and Thornburn) 

0.66 1 , , , , , , , , , 1 

0.64 - J 

■■ i'l 
\l I 

0.62 - 1 



o 0.6- 




Q 5 1 \ \ \ I I I \ \ \ 

■ 10 20 30 40 50 60 70 80 90 100 

Number of case 



Fig 7.14 Number of data versus the resistance factor cD with Pt =3.0 for driven piles in 
mixed soil from North, Central and South of Vietnam using Shmertmann SPT method 



157 



0.35 1 

0.34 - 
0.33 - L 



^ 0.32- 




26 ' ^ ^ ^ ^ ^ ^ ^ ^ ^ 

■ 10 20 30 40 50 60 70 80 90 100 

Number of case 



Fig 7.15 Number of data versus the resistance factor O with Pt =3.0 for driven piles in 
mixed soil from North, Central and South of Vietnam using a-Tomlinson & Nordlund- 
Thurman ( Su from Terzaghi and Peck) 

0.6 r I I I I I I I I I - 

0.58 - i 




Q 44 1 1 1 1 1 1 1 1 1 1 

■ 10 20 30 40 50 60 70 80 90 100 

Number of case 

Fig 7.16 Number of data versus the resistance factor cD with Pt =3.0 for driven piles in 
mixed soil from North, Central and South of Vietnam using X & Nordlund-Thurman ( Su 
from Terzaghi and Peck) 



158 



7.5.5 Recommendations resistance factor for driven pile in Vietnam 

The following correlation between SPT and undrain shear strength Su and friction 
angle are recommended for calculate the nominal capacity of driven pile in 
Vietnam 

• For piles in Cohesionless soil: using the correlation between friction (j) and 
SPT by Peck, Hanson & Thornbum 

• For piles in Cohesive soil: using the correlation between Su and SPT by 
Hara 

• For piles in Mixed soil: using the correlation between Su and SPT by 
Terzaghi and Peck and the correlation between friction (j) and SPT by 
Peck, Hanson & Thornbum 

Table 7.4 shows the recommendation resistance factors for driven piles design in 
Vietnam including North, Central and South of Vietnam and comparing with the 
AASHTO current design specifications to determine the percent increase (+%) or 
decrease (-%) in the factored capacity. For example, the developed resistance 
factor of the SPT-Meyerhof method in sand soil was about 56% greater than the 
factor provided in 2012 AASHTO specifications. For clay soils, the developed 
resistance factor for P-method using all data from Vietnam was found to be 
around 130% or 230%using data from South of Vietnam greater than those 
recommended by AASHTO. For mixed soils, a significant increase of about, 
64%), 80% or 54%) in the resistance factors was observed for P-Nordlund & 
Thurman method in North, Central or all data in Vietnam compared to AASHTO. 
Moreover, an increase in the resistance factors of about 51%, 37%, 9% and 29% 
was obtained for the a -Tomlinson, Nordlund &Thurman in North, Central, South 
and All in Vietnam. 



159 



Table 7.4 Recommendation of Resistance Factor for Driven Pile in Vietnam with Pt = 3.0 



Soil 


Static Method 


AASHTO 
901 9 


O Total 


O North 


O Central 


O South 




Nordlund&Thurman 


0.45 


0.40 (-11%) 


0.39(-13%) 






Sand 


Schmertmann 
SPT 




u.ou 


U.JO 








Meyerhot 
SPT 


0.3 


0.47 (+56%) 


0.47 (+56%) 


- 


- 




a -Tomhnson 


0.35 


0.32 (+8%) 


0.44 (+26%) 


0.88 (+152%) 






a- API 




0.38 


0.36 


0.85 




Clay 


X 


0.4 


0.63 (+58%) 


0.35 (-38%) 


0.78 (+95%) 


- 


P 


0.25 


0.57 (+128%) 


0.52 (+1.08%) 


0.82 (+228%) 


- 




Schmertmann 
SPT 




0.49 


0.47 


0.91 






a -Tomlinson, 
Nordlund&Thurman 


0.35 


0.45 (+29%) 


0.43 (+51%)) 


0.58 (+37%)) 


0.38 (+9%) 




a - API, 
Nordlund& Thurman 




0.46 


0.46 


0.65 


0.28 


Mixed 


Nordlund&Thurman 


0.4 


0.47 (+18%) 


0.47 (+18%) 


0.59 (+48%) 


0.32 (-20%) 




P 

Nordlund&Thurman 


0.25 


0.38 (+52%) 


0.41 (+64%) 


0.45 (+80%) 


0.25 (0%) 




Schmertmann 
SPT 




0.51 


0.54 


0.4 


0.80 



160 



8. Calibration Resistance Factor for Drilled Shafts Vietnam 

In this chapter, resistance factors for drilled Shaft in Vietnam are developed for FHWA 
method and Reese & Wight method. Also the same with driven pile, calibration of the 
resistance factors for each analysis method is presented separately and discussed in detail, 
including histograms and frequency distribution for each case attained using database 
was collected in Vietnam by author. For the resistance factors corresponding to a wide 
range of target reliability indices, a sensitivity analysis is considered in order to provide 
the designer the freedom to select and determine the degree of conservatism in the 
design. Efficiency factors are also provided to appropriately compare the economy of 
different methods. Equivalent factors of safety were back calculated from the developed 
LRFD resistance factors to compare the ASD approach and determine the percentage of 
gain in the pile capacity when using the LRFD approach. All the regionally developed 
resistance factors are thus compared with the current design specifications. 

8.1 Procedure to Calibrate Resistance Factors for Drilled Shaft 

Collect the static load tests and soil profile for Drilled Shaft in North, Central and South 
of Vietnam. 

Calculate the nominal capacity by using FHWA and Reese & Wright method. 
Interpret the static load tests to find the real capacity of drilled shaft and driven piles by 
using 1" and 0.5% D settlement criterion. 
Calculate the bias factor Xri = Rmi / Rni 

Calculate the mean, Xr, and the coefficient of variation, COV, of the random series Xri. 
Calibrate the resistance factor by using First Order Second Method (FORM) and 
First Order Reliability Method (FORM) and Monte Carlo simulation 

8.2 Collection of Drilled Shaft in Vietnam 

The calibration resistance factor process for drilled shaft in Vietnam requires an extensive 
data base. From 2008 to 2012 the author collected 92 static load test and soil profiles for 
drilled shaft from North, Central and South of Vietnam. The list of all piles including 
locations, depth and cross section of piles can be found in table Gl in appendix G. All 
data for drilled shaft from big city in Vietnam such as Hanoi, Haiphong and Saigon 

161 



8.3 Measurement Capacity of drilled Shaft 

1" and 0.5%D settlement's criterion were used to interpret the static load test data 
for driven pile in North, Central and South of Vietnam and the resuh is shown 
detail in Table G2 in appendix G. 

8.4 Nominal Capacity of Drilled Shaft 

8.4.1 Nominal Capacity of Concrete Piles in Mixed Soils 

FHWA method and Reese and Wight methods were used for predicting the design 
nominal capacity of drilled shaft in this researchby using the correlation, 
previously mentioned in Chapter 3, between Nspt and the un-drain shear strength 
Su of clay by Terzaghi and Peck (1967) or Hara (1974) The predicted capacity of 
driven piles in mixed soil is in table G-3 in appendix G. 



162 



2500 



2000 



■§ 1500 



E 

^ 1000 



500 



FHWA method (Su: Terzaghi & Peck ) 

































































































































^' 






















































































































♦ 


► 




























































< 


► 


r 








































































i 






























< 












































(Li 








y- 


=-i 






























































R 




n 








































> 








< 


► 














































— 




































































-* 







































































































































500 1,000 1,500 2,000 2,500 3,000 3,500 

1" Capacity 



Figures 8.1a: Prediction Capacity using FHWA method (Su: T-P) vs. Measure Capacity 
of Drilled Shaft using 1" Criterion in Mixed Soils in Vietnam 



T3 

o 



3500 
3000 
2500 



m 2000 
E 

^ 1500 
^ 1000 
500 




FHWA method (Su: Hara ) 




liiiB 



3i: 



500 1000 1500 2000 2500 3000 3500 

1" Capacity 



Figures 8.1b: Prediction Capacity using FHWA method (Su: Hara) vs. Measure Capacity 
of Drilled Shaft using 1" Criterion in Mixed Soils in Vietnam 



163 



R & W method (Su: Terzaghi & Peck ) 



3000 



2500 

T3 

O 

^ 2000 
E 



a: 

1000 



500 



























































































































































































































































































































































































































































































































































































































































































































































































































































♦ 








— 4 


w 






































































































k- 




















































































































































y 






>- 








n Q 


bn 


V - 




































t . » 


















r - 


















































T ceo 




























































J 




































m 




























































































































































































































































































































> 
































































♦ 






















































-< 


►- 































































































































































































































































































































































































































































































500 1000 1500 2000 2500 3000 3500 

1" Capacity 



Figures 8.1c: Prediction Capacity using R&W method (Su: T-P) vs. Measure Capacity of 
Drilled Shaft using 1" Criterion in Mixed Soils in Vietnam 



R&W method (Su: Hara ) 



T3 

^ 2500 

E 2000 

03 1500 
en 

1000 
500 








— ♦ 


nn 

— — 

^^4- 


9^ 

m 


— i 


. 


— 

it 


m 

^-0.6 


* 


— «t — 



500 1000 1500 2000 2500 3000 

1" Capacity 



Figures 8. Id: Prediction Capacity using R&W method (Su: Hara) vs. Measure Capacity 
of Drilled Shaft using 1" Criterion in Mixed Soils in Vietnam 



164 



T3 
O 



E 
< 



2500 



2000 



1500 



1000 



500 



FHWA method (Su: Terzaghi & Peck 




500 1000 1500 2000 2500 3000 3500 4000 4500 

1" Capacity 



Figures 8.2a: Prediction Capacity using FHWA method (Su: Terzaghi&Peck) vs. 
Measure Capacity of Drilled Shaft using 1" Criterion in Mixed Soils in Vietnam 



3500 
3000 
2500 

T3 

o 

^ 2000 
E 

^ 1500 
X 

Li. 

1000 
500 




FHWA method (Su: Hara ) 















































































































































































































































-C 
































































































7- 


















































































































































































r 




































































































































































>- 






























































































y 


















-A 












< 




























• 








M 




► 


1 








■ 


















































































1 














♦ 
















































































► 




♦ 
























































■ 


■ 








rs 














i 


• 




























































■ 


i 










































































r 
















































































-* 


>- 





































































































































































































































































500 1000 1500 2000 2500 3000 3500 4000 4500 

0.5%D Capacity 



Figures 8.2b: Prediction Capacity using FHWA method (Su: Hara) vs. Measure Capacity 
of Drilled Shaft using 0.5%D Criterion in Mixed Soils in Vietnam 



165 



3500 



3000 



2500 

o 

^ 2000 
E 



R & W method (Su: Terzaghi & Peck ) 



en 



1500 



1000 



500 



























































































































































































































































































































































































































-( 






hi 






f- 
















































































& 


41 












































































































































































< 




















► 














































































































































































y- 
















































































































































>- 






1 


i 










► 






































































n 




























































































• 




1 










































































-i 




4 


K 










































































P 








1 












► 


































































-< 


>- 




















































































i 


y 




1 




















































































■A 


>^ 











































































































































































500 1000 1500 2000 2500 3000 3500 4000 4500 

0.5%D Capacity 



Figures 8.2c: Prediction Capacity using R&W method (Su: T-P) vs. Measure Capacity of 
Drilled Shaft using 0.5%D Criterion in Mixed Soils in Vietnam 



4500 

4000 

3500 

T3 3000 
O 

oJ 2500 
E 

^ 2000 

oa 

a: 1500 
1000 
500 




R&W method (Su: Hara ) 



iiiyi: 




4* 



^: 



2: 



z: 



500 1000 1500 2000 2500 3000 3500 4000 4500 

0.5%D Capacity 



Figures 8. 2d: Prediction Capacity using R&W method (Su: Hara) vs. Measure Capacity 
of Drilled Shaft using 0.5%D Criterion in Mixed Soils in Vietnam 



166 



8.5 Calibration of Resistance Factors for Drilled Shaft 

The same with driven pile, there are three statistical methods including First 
Order Second Moment (FOSM), First Order ReUability Methods (FORM) and 
other advanced methods, such as the Monte Carlo simulation, have been used for 
performing the reliability analyses to find the resistance factor for drilled shaft by 
assuming a lognormal distribution of the load and resistance Probability Density 
Functions (PDFs).Using the E.q 4.47 for FOSM to find the resistance and using 
Matlab program for FORM and Monte Carlo simulation by following the theory 
discussed in chapter 4. 

8.5.1 Resistant factor for drilled shaft in Mixed Soil 

Table 8.1, 8.1a to 8. If shows the bias factor and the calibration resistance factor 
as well as efficiency factor (cp/^.), equivalent factor of safety to ASD and actual 
mean factor of safety for drilled shaft in Mixed soil by FHWA method and 
Reese& Wright for calculating the nominal capacity in North, Central and South 
of Vietnam with 1" and 0.5%D settlement criterion. Figure 8.3 a and 8.3b is an 
example of the histogram and frequency distribution of bias factor X\ and an 
example of resistant factor calibration 92 cases of drilled shaft in mixed soils 
using the FHWA method with correlation between undrain shear strength Su and 
SPT by Terzaghi and Peck and using 1" settlement criterion in Vietnam. The 
other histograms and frequency distributions of bias factor: X\ toXS and resistant 
factor calibration: Ol to 08 corresponding to different method for All data. North 
data, and South data can be found in the figure G-Ml-a to G-M8-d in appendix G 

Table. 8.1 Bias Factor for drilled Shaft in Mixed Soil using FHWA and Reese & Wright method 
with 1" and 0.5% D settlement criterion. 





1" settlement Criterion 


0.5 % D settlementCriterion 


FHWA method 


Reese and Wright 
method 


FHWA method 


Reese and Wright 
method 


Su (T, P) 


Su (Kara) 


Su (T,P) 


Su 
(Kara) 


Su (T,P) 


Su 
(Kara) 


Su (T,P) 


Su 
(Kara) 


^1 


X2 


^3 


^4 


^5 


X6 


X7 




NP-Ml 


1.35 


1.18 


1.26 


1.11 


1.44 


1.26 


1.34 


1.18 


NP-M2 


1.39 


1.22 


1.29 


1.14 


1.47 


1.29 


1.37 


1.21 



167 



Table 8.1 (cont.) 



NP-M3 


1.05 


0.94 


0.99 


0.89 


1.33 


1.19 


1.26 


1.13 


NP-M4 


1.07 


0.95 


1.01 


0.91 


1.33 


1.19 


1.26 


1.13 


NP-M5 


1.23 


1.10 


1.16 


1.04 


1.40 


1.25 


1.32 


1.19 


NP-M6 


1.37 


1.28 


0.92 


0.88 


1.98 


1.85 


1.33 


1.27 


NP-M7 


1.36 


1.27 


0.91 


0.87 


1.57 


1.47 


1.06 


1.01 


NP-M9 


1.15 


0.96 


1.06 


0.90 


1.52 


1.26 


1.40 


1.18 


NP-MIO 


1.30 


1.08 


1.20 


1.01 


1.59 


1.32 


1.47 


1.23 


NP-Ml 1 


1.37 


1.25 


1.27 


1.56 


1.71 


1.56 


1.59 


1.95 


NP-M12 


1.24 


1.13 


1.15 


1.41 


1.41 


1.29 


1.31 


1.60 


NP-Ml 3 


1.49 


1.36 


1.40 


1.28 


1.72 


1.57 


1.62 


1.48 


NP-Ml 4 


1.02 


0.80 


1.06 


0.83 


1.14 


0.90 


1.19 


0.93 


NP-Ml 5 


1.01 


0.79 


1.06 


0.82 


1.14 


0.89 


1.20 


0.93 


NP-Ml 6 


1.50 


0.96 


1.45 


0.94 


1.66 


1.06 


1.59 


1.04 


NP-Ml 7 


1.55 


1.00 


1.50 


0.97 


1.69 


1.08 


1.63 


1.06 


NP-Ml 8 


1.54 


1.10 


1.15 


0.88 


1.94 


1.38 


1.45 


1.11 


NP-Ml 9 


1.39 


1.00 


1.04 


0.80 


1.79 


1.28 


1.34 


1.03 


NP-M20 


1.54 


1.10 


1.15 


0.88 


1.92 


1.37 


1.43 


1.10 


NP-M21 


1.30 


0.93 


0.97 


0.74 


1.65 


1.18 


1.23 


0.95 


NP-M22 


1.15 


0.85 


0.77 


0.63 


1.46 


1.08 


0.98 


0.79 


NP-M23 


1.27 


1.13 


0.86 


0.79 


1.59 


1.42 


1.07 


0.99 


NP-M27 


1.11 


0.90 


0.79 


0.67 


1.40 


1.12 


0.99 


0.85 


NP-M28 


1.34 


1.10 


0.95 


0.83 


1.61 


1.33 


1.15 


1.00 


NP-M29 


1.02 


0.72 


1.14 


0.78 


1.09 


0.77 


1.23 


0.84 


NP-M30 


1.73 


1.09 


1.29 


1.09 


2.52 


1.58 


1.88 


1.58 


NP-M3 1 


0.85 


0.76 


0.69 


0.63 


0.94 


0.84 


0.76 


0.69 


NP-M32 


0.83 


0.74 


0.67 


0.61 


0.95 


0.85 


0.77 


0.70 


NP-M35 


1.04 


0.92 


0.89 


0.80 


1.17 


1.04 


1.00 


0.90 


NP-M36 


0.90 


0.80 


0.77 


0.70 


1.09 


0.97 


0.93 


0.85 


NP-M37 


1.24 


1.11 


1.06 


0.96 


1.55 


1.38 


1.33 


1.20 


NP-M38 


0.99 


0.89 


0.85 


0.77 


1.11 


0.99 


0.95 


0.86 


NP-M39 


1.28 


1.14 


1.09 


0.99 


1.64 


1.46 


1.40 


1.27 


NP-M40 


1.65 


1.21 


0.92 


0.76 


1.86 


1.36 


1.03 


0.86 


NP-M41 


1.55 


1.14 


0.86 


0.72 


1.79 


1.32 


1.00 


0.83 


NP-M42 


1.27 


1.23 


0.88 


0.86 


1.45 


1.40 


1.00 


0.98 


NP-M43 


1.26 


1.22 


0.87 


0.85 


1.44 


1.39 


1.00 


0.97 


NP-M44 


1.23 


1.19 


0.85 


0.84 


1.42 


1.38 


0.98 


0.96 


NP-M45 


1.29 


1.25 


0.89 


0.87 


1.47 


1.42 


1.02 


0.99 


NP-M46 


1.25 


1.21 


0.87 


0.85 


1.43 


1.39 


0.99 


0.97 


NP-M47 


1.36 


1.32 


0.94 


0.92 


1.51 


1.46 


1.04 


1.02 


NP-M48 


1.07 


1.04 


0.74 


0.72 


1.17 


1.14 


0.81 


0.80 



168 



Table 8.1 (cont.) 



NP-M49 


1.17 


1.14 


0.81 


0.80 


1.39 


1.35 


0.96 


0.94 


NP-M50 


1.21 


1.00 


0.88 


0.77 


1.54 


1.28 


1.12 


0.98 


NP-M5 1 


1.33 


1.14 


1.23 


1.06 


1.69 


1.44 


1.55 


1.34 


NP-M52 


1.13 


0.97 


1.26 


1.08 


1.35 


1.17 


1.52 


1.29 


NP-M53 


1.23 


0.91 


1.10 


0.83 


1.43 


1.05 


1.28 


0.97 


NP-M54 


0.94 


0.87 


0.83 


0.77 


1.03 


0.95 


0.91 


0.84 


NP-M55 


1.10 


0.98 


0.80 


0.74 


1.23 


1.10 


0.89 


0.82 


NP-M56 


1.09 


0.97 


0.79 


0.73 


1.23 


1.10 


0.89 


0.82 


NP-M57 


0.98 


0.87 


0.71 


0.65 


1.11 


0.99 


0.81 


0.74 


NP-M58 


1.08 


0.92 


0.87 


0.76 


1.30 


1.11 


1.05 


0.92 


NP-M59 


0.78 


0.66 


0.63 


0.55 


0.88 


0.75 


0.71 


0.62 


NP-M60 


1.66 


1.39 


1.11 


0.98 


2.36 


1.98 


1.59 


1.40 


NP-M61 


2.53 


2.12 


1.70 


1.50 


3.15 


2.64 


2.11 


1.87 


NP-M62 


1.92 


1.61 


1.29 


1.14 


2.36 


1.98 


1.59 


1.40 


NP-M63 


1.73 


1.34 


1.08 


0.92 


2.20 


1.70 


1.38 


1.16 


NP-M64 


1.66 


1.32 


1.05 


0.90 


2.26 


1.79 


1.43 


1.23 


NP-M65 


1.55 


1.23 


0.98 


0.85 


2.14 


1.70 


1.36 


1.17 


NP-M66 


1.78 


1.47 


1.15 


1.01 


2.22 


1.84 


1.43 


1.26 


NP-M67 


1.90 


1.55 


1.23 


1.08 


2.23 


1.83 


1.45 


1.27 


NP-M68 


1.61 


1.11 


1.39 


1.01 


2.13 


1.48 


1.85 


1.34 


NP-M69 


1.23 


0.88 


1.06 


0.79 


2.16 


1.54 


1.87 


1.39 


NP-M70 


1.87 


1.63 


1.09 


1.00 


2.39 


2.08 


1.40 


1.29 


NP-M71 


1.49 


1.28 


0.83 


0.76 


1.68 


1.44 


0.94 


0.86 


NP-M72 


1.68 


1.08 


1.36 


0.94 


2.09 


1.34 


1.69 


1.16 


NP-M73 


2.10 


1.47 


1.85 


1.34 


2.12 


1.48 


1.86 


1.35 


NP-M74 


1.66 


1.04 


1.38 


0.92 


2.12 


1.32 


1.75 


1.17 


NP-M75 


1.45 


1.08 


1.13 


0.90 


1.62 


1.21 


1.26 


1.00 


NP-M76 


1.41 


1.07 


1.07 


0.87 


1.57 


1.19 


1.19 


0.96 


NP-M77 


1.43 


1.09 


1.09 


0.88 


1.58 


1.20 


1.20 


0.97 


NP-M78 


1.44 


1.09 


1.09 


0.88 


1.62 


1.23 


1.23 


0.99 


NP-M79 


0.96 


0.51 


0.81 


0.46 


1.12 


0.60 


0.94 


0.54 


NP-M80 


1.00 


0.62 


0.75 


0.52 


1.05 


0.65 


0.79 


0.54 


NP-M81 


1.37 


1.01 


0.89 


0.72 


1.65 


1.22 


1.07 


0.87 


NP-M82 


1.27 


0.88 


1.06 


0.77 


1.51 


1.05 


1.27 


0.93 


NP-M83 


1.34 


0.93 


1.12 


0.82 


1.57 


1.09 


1.31 


0.96 


NP-M84 


1.37 


0.95 


1.15 


0.84 


1.53 


1.07 


1.29 


0.94 


NP-M85 


1.04 


0.63 


0.93 


0.58 


1.20 


0.72 


1.07 


0.67 


NP-M86 


0.84 


0.50 


0.93 


0.47 


0.91 


0.55 


1.00 


0.51 


CP-MI 


1.63 


1.04 


1.26 


0.88 


2.51 


1.60 


1.94 


1.35 


CP-M2 


1.94 


1.22 


1.24 


0.90 


2.93 


1.85 


1.88 


1.36 



169 



Table 8.1 (cont.) 



SP-M3 


1.04 


0.94 


1.17 


1.05 


1.23 


1.12 


1.39 


1.25 


SP-M4 


1.10 


0.98 


1.24 


1.09 


1.15 


1.02 


1.29 


1.13 


SP-Mll 


0.90 


0.51 


0.90 


0.51 


0.97 


0.54 


0.97 


0.54 


SP-M12 


1.64 


1.06 


0.93 


0.71 


1.89 


1.22 


1.07 


0.82 


SP-M13 


1.02 


0.66 


0.58 


0.44 


1.26 


0.81 


0.71 


0.54 


SP-M14 


1.07 


0.71 


0.67 


0.51 


0.88 


0.59 


0.56 


0.42 


SP-M15 


0.86 


0.57 


0.55 


0.41 


1.08 


0.71 


0.68 


0.51 


SP-M16 


0.89 


0.71 


0.73 


0.61 


1.01 


0.81 


0.83 


0.69 


SP-M17 


0.93 


0.74 


0.76 


0.63 


1.10 


0.88 


0.91 


0.75 



170 



Lamdal AIIMixed data 
Normal 

Lognormal 




1.4 1.6 1.1 
Bias Factor 



Figure 8.3a. Histogram and frequency distribution of bias factor ^1 for 92 cases of drilled shaft 
in Mixed soils using the FHWA method (Su: Terzaghi, Peck) and using 1" criterion in Vietnam 



1.4 
1.3 
1.2 

e 1.1 

Q 

O 1 



8 0.9 



B 

if) 
o 

DC 



0.8 
0.7 
0.6 
0.5 
0.4 









Reliability Index, p 



Figure 8.3b. Resistance factor calibration for 92 cases of drilled shaft in Mixed soils using the 
FHWA method (Su: Terzaghi, Peck) and using 1" criterion in Vietnam 



171 



Table S.laSummary of calibration resistance factorfor drilled shaft using FHWA and Reese & 



Wright method wit h 1" criterion settlement in North, Center and South of Vietnam 





rn w/\ met 


10 d 


Reese and Wright method 


oU ^^ 1 crzdgni, r ecK^ 




ou 1 erzagni, r ecK ) 


ou (^riaraj 




fh9 
^yz 




fh4 


Total 


Mean 


1 '^1 
1 .J 1 


1 04 


1 09 
1 .uz 


S/^ 
U.oO 


92 
cases 


stand 


U. JZ 


n 97 


94 


9 1 
U.Z 1 


cov 




n 9s 

U.Z J 


91 
U.Z J 


9S 
U.Z J 


p =2.33 


FOSM 


U.oZU 


U.Ut 1 


ASS 


S10 
U. J jU 


FORM 


n Q9n 


U. / lU 


71A 
U. / JO 


sss 
U.JO J 


MC 




n 714 

U. / If 


U. /4Z 


U.3V1 




U. / 1 


U.Oo 


79 
U. /Z 


AO 

u.oy 






1 0'? 


1 SS 


9 H 
Z.J J 




1 OS 


9 01 

Z.U 1 


1.90 


1.99 


P=3 


FOSM 


0.665 


0.513 


0.532 


0.425 


FORM 


0.770 


0.592 


0.622 


0.490 


MC 


0.775 


0.597 


0.629 


0.493 




0.51 


0.49 


0.52 


0.50 


FS 


2.07 


2.68 


2.58 


3.23 


FSx>. 


2.71 


2.79 


2.65 


2.77 



1 Efficiency factor lEquivalent factor of safety to ASD 3 Actual mean factor of safety 4 Monte Carlo simulation 



Table8. lb Summary of calibration resistance factor for drilled shaft using FHWA and Reese & 



Wright method wit h 1" criterion settlement in North of Vietnam 





FHWA method 


Reese and Wright method 


Su (Terzaghi, Peck) 


Su (Hara) 


Su (Terzaghi, Peck) 


Su (Hara) 


Ol 


02 


03 


04 


North 


Mean 


1.33 


1.07 


1.04 


0.88 


92 
cases 


stand 


0.31 


0.26 


0.23 


0.20 


cov 


0.23 


0.24 


0.22 


0.23 


p =2.33 


FOSM 


0.853 


0.676 


0.681 


0.562 


FORM 


0.950 


0.755 


0.758 


0.625 


MC 


0.966 


0.778 


0.765 


0.641 




0.73 


0.73 


0.74 


0.73 


FS 


1.42 


1.77 


1.80 


2.15 


FSx}i 


1.89 


1.89 


1.87 


1.88 


p=3 


FOSM 


0.690 


0.545 


0.554 


0.455 


FORM 


0.804 


0.625 


0.640 


0.528 


MC 


0.822 


0.625 


0.649 


0.543 




0.62 


0.58 


0.62 


0.62 


FS 


1.67 


2.20 


2.12 


2.53 


FSx>. 


2.22 


2.35 


2.20 


2.22 



172 



Table 8.1c Summary of calibration resistance factor for drilled shaft using FHWA and Reese & 



Wright method wit h 1" criterion settlement in South of Vietnam 





FHWA method 


Reese and Wright method 


k>u 1 erzagni, r ecK ) 


ou (^riaraj 


ou 1 erzagni, r ecK ) 


ou (^riaraj 


fhl 






fhzl 


South 


Mean 


1 

1 .Uj 


u. / / 




u.oo 


10 

cases 


stand 




n 1 Q 


U.Zj 


U.Zj 


cov 


U.Zj 


U.Zj 


u.zy 


U.JO 


p =2.33 


FOSM 


U.Ooz 


n zi7A 


n 478 


n 1 1 7 

U.J 1 / 


FORM 


u. / ou 


U. J 


U. JZ J 


U. J jU 


Monte 


u. /oo 




U.310 




(p/A, 


U. / J 


n A7 
u.o / 


u.oz 


U.J 1 


FS 


1 80 






4 HQ 


FSxX 


1.89 


2.05 


2.22 


2.71 


P=3 


FOSM 


0.553 


0.382 


0.375 


0.238 


FORM 


0.640 


0.445 


0.427 


0.265 


Monte 


0.648 


0.431 


0.426 


0.259 




0.62 


0.56 


0.51 


0.39 


FS 


2.12 


3.19 


3.23 


5.30 


FSx>. 


2.23 


2.44 


2.70 


3.52 



North South and Center of Vietnam 

1.31 ■ Phi ■phi/lamda ■ bias factor 



1.04 1.02 




1 2 3 4 

Figure 8.4a. Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 1" criterion settlement in 
North, Center and South of Vietnam 



173 



North of Vietnam 

■ Phi ■ Phi/Lamda Lamda 




1 2 3 4 



Figure 8.4b. Resistance factor, efficiency factor,equivaIent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 1" criterion settlement in 
North of Vietnam 



South of Vietnam 

■ Phi ■ Phi/Lamda ■ Lamda 

1.05 



0.84 




1 2 3 4 



Figure 8.4c. Resistance factor,efficiency factor,equivaIent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 1" criterion settlement in 
South of Vietnam 



174 



Table 8. Id Summary of calibration resistance factor for drilled shaft using FHWA and Reese & 



Wright method wit h 0.5%D settlement in North, Center and South of Vietnam. 





FHWA method 


Reese and Wright method 


Sill rXpryfiolii PppIc^ 


Su fHara"* 


Sill rXpryac^hi PppV^ 


Su rHara"* 




A.6 




X8 


Total 


Mean 


1.58 


1.25 


1.23 


1.03 


92 
cases 


stand 


46 


37 


32 


29 


cov 


0.29 


0.29 


0.26 


0.28 


p =2.33 


FOSM 


900 


718 


743 


604 


FORM 


0.975 


0.780 


0.820 


0.660 


Monte 


0.988 


0.786 


0.824 


0.623 




0.63 


0.63 


0.67 


0.61 


FS 


1.39 


1.75 


1.67 


2.21 


FSxA 


2.20 


2.19 


2.05 


2.27 


P=3 


FOSM 


0.707 


0.564 


0.592 


0.478 


FORM 


0.795 


0.635 


0.675 


0.542 


Monte 


0.801 


0.641 


0.679 


0.548 


cp/A, 


0.51 


0.51 


0.55 


0.53 


FS 


1.72 


2.15 


2.02 


2.51 


FSxX 


2.71 


2.69 


2.49 


2.58 



Table 8.1eSummary of calibration resistance factor for drilled shaft using FHWA and Reese & 
Wright method wit h 0.5%D settlement in North of Vietnam. 





FHWA method 


Reese and Wright method 


Su (Terzaghi, Peck) 


Su (Hara) 


Su (Terzaghi, Peck) 


Su (Hara) 


X5 


X6 


XI 


?.8 


North 


Mean 


1.60 


1.29 


1.25 


1.05 


80 
cases 


stand 


0.43 


0.35 


0.30 


0.27 


cov 


0.27 


0.27 


0.24 


0.26 


p =2.33 


FOSM 


0.957 


0.768 


0.787 


0.647 


FORM 


1.050 


0.850 


0.875 


0.713 


Monte 


1.072 


0.850 


0.873 


0.730 


(p/A 


0.67 


0.66 


0.70 


0.69 


FS 


1.28 


1.62 


1.58 


1.88 


FSxA 


2.05 


2.08 


1.96 


1.98 


P=3 


FOSM 


0.761 


0.610 


0.634 


0.517 


FORM 


0.865 


0.693 


0.725 


0.586 


Monte 


0.887 


0.697 


0.731 


0.615 


(p/A 


0.56 


0.54 


0.59 


0.59 


FS 


1.55 


1.97 


1.88 


2.24 


FSx?. 


2.48 


2.54 


2.34 


2.35 



175 



Table 8. If Summary of calibration resistance factor for drilled shaft using FHWA and Reese & 



Wright method wit h 0.5%D settlement in South of Vietnam. 





FHWA method 


Reese and Wright method 


Sill rXpryfiolii PppIc^ 


Su fHara"* 


Sill rXpryac^hi PppV^ 


Su rHara"* 




A.6 






South 


Mean 


1.17 


0.86 


0.93 


0.74 


10 

cases 


stand 


29 


23 


28 


29 


cov 


0.25 


0.27 


0.30 


0.39 


p =2.33 


FOSM 


728 


512 


528 


348 


FORM 


0.798 


0.560 


0.580 


0.365 


Monte 


0.807 


0.563 


0.574 


0.364 




0.69 


0.66 


0.61 


0.49 


FS 


1.70 


2.44 


2.39 


3.78 


FSxA 


2.00 


2.09 


2.24 


2.79 


P=3 


FOSM 


0.584 


0.407 


0.414 


0.261 


FORM 


0.678 


0.460 


0.460 


0.280 


Monte 


0.671 


0.464 


0.465 


0.282 


cp/A, 


0.57 


0.54 


0.50 


0.38 


FS 


2.05 


2.96 


2.96 


4.88 


FSxX 


2.41 


2.53 


2.76 


3.61 



North South and Center of Vietnam 

]^ 58 ■ Phi ■ phi/lamda bias factor 



1-25 1.23 




5 6 7 8 

Figure 8.5a. Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 0.5% D criterion 
settlement in North, Center and South of Vietnam 



176 



North of Vietnam 

1.60 ■ Phi ■ Phi/Lamda ■ Lamda 




5 6 7 8 



Figure 8.5b. Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 0.5% D criterion 
settlement in North of Vietnam 

South of Vietnam 

■ Phi ■ Phi/Lamda ■ Lamda 

1.17 



0.93 




5 6 7 8 

Figure 8.5c. Resistance factor, efficiency factor, equivalent factor of safety to ASD for 
drilled shaft using FHWA and Reese & Wright method with 0.5% D criterion 
settlement in South of Vietnam 



177 



8.5.2 Statistical sample size requirements for calibration the resistance factor for drilled 
shafts in Vietnam 

To calibrate the resistance factor for drilled shafts requires collecting a certain number of the 
static load tests and soil profiles data. To find out how many data are needed for calibration the 
resistance factors, a number of bias factor data sets from 5 data to 80 data with increment of one 
data was randomly picked up 100 times from 92 data for drilled shafts and each time pick up the 
resistance factors was calibrated by using Monte-Carlo simulation method and mean value for 
each set of data was calculated. Figure 8.4, 8.5 and 8.6 show the number of data sets versus the 
resistance factor for drilled shafts using FHWA method with Su from Hara, Reese and Wright 
method with Su from Terzaghi and Peck and FHWA method with Su from Hara. From the result, 
a number of data is need for calibration for resistance factor is 30 data for drilled shafts since a 
number of data more than 30 data, the resistance factors calculated are almost the same. 



0.68 - / 




0.58 - 



10 20 30 40 50 60 70 80 

Number of data 

Fig 8.6 Number of data versus the resistance factor O with Px =3.0 for drilled shaft (using the 
FHWA method and Su from Hara) 



178 



0.7 




Number of data 

Fig 8.7 Number of data versus the resistance factor <!> with px =3.0 for drilled shaft using the Reese 
and Wright method (Su from Terzaghi and Peck) 

0.6 1 \ \ \ \ \ \ \ 



0.58 




0.48' ' ' ' ' ' ' ' ' 

10 20 30 40 50 60 70 80 

Number of data 

Fig 8.8 Number of data versus the resistance factor cD with px =3.0 for drilled shaft using the Reese 
and Wright method (Su from Hara) 



179 



9. Conclusions and Recommendation 
9.1 Summary of Research 

Deep foundation data from different locations inNCHRP 507 report including 
368 dynamic load tests in which 240 cases with end of driving (EOD) capacities 
and 128 cases with beginning of strike (BOR) capacities, and 131 static load tests 
for concrete piles with 19 cases in cohesive soils, 37 cases in cohesionless soils, 
and 85 cases in mixed soil. The U.S. database was used to calibrate the resistant 
factors of piles to examine the location dependency. 

Eight different static analysis methods: a- Tomlinson, a-API, X, P, Nordlund, 
Thurman, Meyerhof SPT, and the Shmertmann SPT method were used for 
calculating the design nominal capacity of driven piles. Resistance factor 
calibration was conducted based on the Vietnamese database includes 273 static 
load tests and soil profiles for driven piles in different soil types in North, Central 
and South Vietnam. Chin's method, Davisson's method, and the 1" settlement 
criterion were used in the interpretation of load test results for driven piles 
capacity in Vietnam. The FHWA method and Reese & Wright method were used 
to calculate the design nominal capacities of drilled shafts in Vietnam. The LRFD 
calibration was conducted based on 92 static load tests and soil profiles for drilled 
shafts in mixed soil in North, Central, and South Vietnam. The 1" and 0.5% of the 
pile diameter settlement criterions were used to determine the capacity of drilled 
shafts. 

The calibration of resistance factors for deep foundations was performed using 
NCHRP 507 and Vietnamese database. Reliability based analyses using the First 
Order Second Moment (FOSM) method, the First Order Rehability Method 
(FORM), and the Monte Carlo (MC) simulation method were conducted to 
calibrate the resistance factors (O). Following ASSHTO 2012, the resistance 



180 



factors were evaluated at the target reliability index (Pt) of 2.33 for redundant 
piles (defined as 5 or more piles per pile cap (group)), which corresponds to a 
failure probability of 1%, and for the target reliability index (Pt) of 3.0 for non- 
redundant piles (defined as 4 or less piles per pile cap), which corresponds to a 
failure probability of 0.1%. 

9.2 Major Outcomes and Conclusions 

• Resistance factors are calibrated using three reliability analysis methods, 
including FOSM, FORM, and Monte Carlo Simulations. Of the three methods 
used the Monte Carlo and FORM methods yielded close results that encourage 
assurance. This being the case, the resistance factors given by the Monte Carlo 
simulations are chosen for the development of deep foundation design in this 
work. 

• The resistance factors evaluated for PDA-CAP WAP data, using the NCHRP 507 
data at EOD and BOR, vary with location. 

• In general, the resistance factors found in this work for a specific/separate 
location are much different from the resistance factors given by the "lumped" or 
combined locations from the NCHRP 507 report and AASHTO specifications. 

• When using semi-empirical methods and in-situ methods, the resistance factors 
for concrete pile design from Florida and Louisiana are only slightly different 
from the resistance factors recommended in NCHRP 507 report since most of the 
collected data is from Florida and Louisiana. 

• For deep foundation design, no LFFD codes are available in Vietnam. This study 
provides the first development of resistant factors for driven piles and drilled 
shafts in Vietnam. The resistance factors evaluated in this study should be reliable 



181 



since they based on extensive collections of static load tests and soil profiles in 
North, South, and Central Vietnam. In chapter 7 the resistance factors were 
developed for driven pile design based upon detailed calibration with eight 
different methods for the capacities of piles in sand, clay, and mixed soil from 
different locations in Vietnam. The resistance factors for drilled shaft capacities 
may be found in chapter 8 and were developed based upon calibration with the 
FHWA and Reese & Wright methods in sand, clay and mixed Soil. 

• The resistance factors, calibrated from the NCHRP 507 report and Vietnamese 
data, were determined to be strongly dependent upon design methods, deep 
foundation types, methods of exploration, testing of geo-materials, geo-material 
types, and geological formation. 

• The regionally developed resistance factors were also compared to those provided 
in the design specifications to determine the percent increase or decrease in the 
factored capacity. 

9.3 Recommendations 

• AASHTO's resistance factors for application to all state DOTs or Vietnam will 
lead to under or over design of deep foundations. "So one size does not fit all" 
and different regions must have their own set of resistance factors. 

• The resistance factors (O) for driven piles and drilled shafts in Vietnam, given in 
chapter 7 and 8, are recommended for design of deep foundations in Vietnam. 



182 



.4 Recommendations for Future Research 

Continue to collect more static load tests (preferably with strain gauge 
instrumentation), PDA, and soil profiles for driven piles and drilled shafts in 
Central and South Vietnam in cohesive and cohesionless soil. 

Use the collected load test and soil exploration data to validate a well verified 
finite element analysis (FEA) program that may be used to study the load- 
deformation behavior of deep foundations. 

Develop/calibrate resistance factors for deep foundation service limit states using 
both the finite element method (FEM) and the collected deep foundation test data 
for both vertical and horizontal displacements. 



183 



APPENDIX A 
Calibration Resistance Factor by Using FORM 
for Driven Pile using CAPWAP Method 



4 































— - 































— 




—data 

" Normal distribution 
— Lognormal distribufion 






























i 


I 
































N, 


















— y \ 
r i 

. Jr 




























T 




l— 1 V 


^ 1 1 


T - n 


n 




n 



0.5 1 1.5 2 2 5 3 3,5 4 4.5 5 55 

Rdavisson/Rca pwa p 

Figure A- la Frequency Distribution for All 365 CAPWAP (BOR+EOD) Cases 




Reliability Index, (i 

Figure A- lb Resistance Factor Calibration from 365 CAPWAP (BOR+EOD) Case 



184 




0.5 1 1.5 2 2.5 

Rdavisson/Rcapwap 

gure A-2a Frequency Distribution for 14 CAPWAP (BOR+EOD) Cases 

Alabama 

1 




5 6 7 

Reliability Index, |i 



10 



Figure A-2b Resistance Factor Calibration from 14 
CAPWAP (BOR+EOD) Cases in Alabama 



186 




2 2.5 
Rdavisson/Rcapwap 



Figure A-3a Frequency Distribution for 13 
CAPWAP (BOR+EOD) Cases in California 



1 1.5 2 2.5 3 3.5 4 4.5 

Reliability Index, p 

Figure A-3b Resistance Factor Calibration from 13 

CAPWAP (BOR+EOD) Cases in California 



187 




0.8 1 1.2 1.4 

Rdavission/Rcapwap 



Figure A-4a Frequency Distribution for 8 
CAPWAP (BOR+EOD) Cases in Canada 




2 3 4 
Reliability Index, p 

Figure A-4b Resistance Factor Calibration from 8 
CAPWAP (BOR+EOD) Cases in Canada 



188 



data 

normal distribution 

lognormal distribution 




2 2.5 3 3.5 
Rdavission/Rcapwap 



4.5 



Figure A-5a Frequency Distribution for 16 
CAPWAP (BOR+EOD) Cases in S Carolina 




2 2.5 3 3.5 

Reliability Index, [1 



Figure A-5b Resistance Factor Calibration from 
16 CAPWAP (BOR+EOD) Cases in S Carolina 



189 



m 

e 

a. 



1 












- — — ~ 
















E 




















data 

normal distribution 

tog normal distribution 






















































.... 






























s 

X 

k \. 








^ / 


























\ 


\ 












/r 













































0.5 1 1.5 2 2.5 3 3.5 

Rdavisson/Rcapwap 

Figure A-6a Frequency Distribution for 107 
CAPWAP (BOR+EOD) Pile-Cases in Florida 




Reliability Index, \\ 
Figure A-6b Resistance Factor Calibration from 
107 CAPWAP (BOR+EOD) pile-cases in Florida 



190 



16 
14 



12 



n 

Q 
a. 



-data 

- normal distribution 

- lognormal distribution 




4 6 8 

Rdavisson/Rcapwap 



Figure A-7a Frequency Distribution for 
22 CAPWAP (BOR+EOD) Cases in Louisiana 




1.5 2 2.5 3 

Reliability Index, (1 
Figure A-7b Resistance Factor Calibration from 
22 CAPWAP (BOR+EOD) Cases in Louisiana 



4.5 



191 



i 







i 








I 1 

\ \ 
\ E 
: [ 




— 


























' data 

normal distribution 

lognormal distribution 




























































I 






- 


























[ 










/ 


































/ 


/ 




























i 
[ 




































S 


■ 






E 
E 

E 

* r 










- ^ 

y 
































-\ 















I ' I I I I I i 1 III I 

0.5 1 1.5 2 2.5 3 3.5 4 4.5 

Rdavisson/Rcapwap 



Figure A-8a Frequency Distribution for 
17 CAPWAP (BOR+EOD) Cases in Massachusetts 




1 2 3 4 5 6 7 

Reliability Index, |l 

Figure A-8b Resistance Factor Calibration from 

17 CAPWAP (BOR+EOD) Cases in Massachusetts 



192 



25 



20 



^ 15 



5 



























data 

normal distribution 

lognormaE distribulion 












































































> 




S 








^ / 





























0.5 1 1.5 2 2.5 

Rdavisson/Rcapwap 

Figure A-9a Frequency Distribution for 
9 CAPWAP (BOR+EOD) Cases in Nebraska 




Reliability Index, p 
Figure A-9b Resistance Factor Calibration from 
9 CAPWAP (BOR+EOD) Cases in Nebraska 



193 



























1 L 


data 

Normal distribution 

Lognormal distributior 


= 























































































^ 






X ^ 


V- 


























V 

N 


S 








/ 


















■■•^ 









.5 1 1.5 2 2.5 3 3.5 

Rdavission/Rcapwap 

Figure A- 10a Frequency Distribution for 

7 CAPWAP (BOR+EOD) Cases in Oklahoma 




1 2 3 4 5 6 7 3 

Reliability Index, |1 

Figure A- 10b Resistance Factor Calibration from 
7 CAPWAP (BOR+EOD) Cases in Oklahoma 



194 



25 



5 



















data 

Normal distribution 
Log normal distribution 


































/ 

/ 






\ 

\ 
Ik \ 






/ 


/ / 
/ / 

' / 
1 


/ 










>i 

\ 

. \ 
V \ 


it \ 












4 

// 

/ / 

y / 
















\ \ 


\ 








~ U^»^ 



0.5 1 1,5 2 2.5 

Rdavisson/Rcapwap 

Figure A-lla Frequency distribution for 15 CAPWAP (BOR+EOD) Cases in Ortanrio 




Reliability Index, |1 
Figure A-1 lb Resistance Factor Calibration from 
15 CAPWAP (BOR+EOD) Cases in Ortanrio 



195 



30 



25 




0123456789 10 
Reliability Index, ^ 

Figure A- 12b Resistance Factor Calibration from 

12 CAPWAP Cases in Pennsylvania 



196 



16 



14 



12 



^ 10 

ft 



— data 

— Normal distribution 

— Lognormal distribution 




1.5 2 2.5 3 

Rdavisson/Rcapwap 



Figure A- 13a Frequency Distribution for 
27 CAPWAP (BOR+EOD) Cases in Wisconsin 



2 3 4 

Reliability Index, (i 



Figure A- 13b Resistance Factor Calibration from 
27 CAPWAP (BOR+EOD) Cases in Wisconsin 



4.5 




197 





























— 


































data 

normal distribution 

lognormal distribution 












-> 
















i_ 










































\ ^ 
\ \ 


\ 

\ 




























\ \ 
\ \ 
\ \ 










/ 




























\ 

\ 

\ \ 








/ 










































r-r-i 



0.5 1 1 5 2 2 5 3 3.5 

Rdavisson/Rcapwap 

gure A- 14a Frequency Distribution for All 240 CAPWAP (BOR) Cases 




1 2 3 4 5 6 7 8 

Reliability Index, |3 
Figure A- 14b Resistance Factor Calibration from 
240 CAPWAP (BOR) Cases 



198 

















- — 














lognoimal distribution 

normal distribution 

data 
















- — — 




















































s 

Nt 






^/ 





















0.5 1 1.5 2 2.5 



Rdavisson/Rcapwap 

Figure A- 15a Frequency Distribution for 9 CAPWAP (BOR) Cases in Alabama 




Reliability Index, (1 
Figure A- 15b Resistance Factor Calibration from 
9 CAPWAP (BOR) Cases in Alabama 



199 



















• 








































( 

( 


lata 

lormal distribution 
ognormal distribution 


















































































/ 








\ N 
V s 


\ 






it 


/ 


7 












\ 

\ 










/ 


A 


























\ 




s 










■ / 

y k 
^ J 








































_ n 



0.5 1 1.5 2 2.5 3 3.5 

Rdavission/Rcapwap 



Figure A- 16a Frequency Distribution for 85 CAPWAP (BOR) Cases in Florida 




Reliability Index, f! 
Figure A- 16b Resistance Factor Calibration from 
85 CAPWAP (BOR) Cases in Florida 



200 



25 



20 



data 

normal distribution 
lognormal distribution 




1.5 2 2.5 

Rdavission/Rcapwap 



3.5 



Figure A- 17a Frequency Distribution for 15 CAPWAP (BOR) Cases in Louisiana 

1.5 r 




2.5 3 
Reliability Index, p 

Figure A- 17b Resistance Factor Calibration from 
15 CAPWAP (BOR) Cases in Louisiana 



4.5 



201 



40 
35 
30 



- Normal distribution 
■ Lognormal distribtion 
-data 




1 1.1 1.2 1.3 1,4 1.5 

Rdavission/Rcawap 

Figure A- 18a Frequency Distribution for 15 CAPWAP (BOR) Cases in Ontario 

1.5Q 




2 3 4 

Reliability Index, p 



Figure A- 18b Resistance Factor Calibration from 
15 CAPWAP (BOR) Cases in Ontario 



202 











1 


































data 

Normal distribution 

^— - Lognomnal distribution 








































































































































































^^^^ 












i 





























J I I I I I i I I s I I ! 1 I 

0.8 1 1.2 1.4 1.6 1.8 

Rd a V is si o n/Rca pwa p 



Figure A- 19a Frequency Distribution for 13 CAPWAP (BOR) Cases in S. Carolina 




Reliability Index, fl 
Figure A- 19b Resistance Factor Calibration from 
13 CAPWAP (BOR) Cases in S. Carolina 



203 



25 



20 



gl5 

15 



5 







1 




1 












— . ™ — — . 
















Data 

normal distribution 

lognormal distribution 


















/ 

/ 

/ 


/\ 


\ 


\ 

\ 
































/ 








\ 




\ 

. \ 







































0.5 1 1.5 2 2.5 

Rdavisson/Rcapwap 



Figure A-20a Frequency Distribution for 15 CAPWAP (BOR) Cases in Wisconsin 




0123456789 
Reliability Index, [1 

Figure A-20b Resistance Factor Calibration from 

15 CAPWAP-BOR Cases in Wisconsin 



204 





! 


































data [ 


[n 


Normal dtstribution 

Log normal distribution [ 










1 






























■^1 \\\\\\\\ 
>* 1 n 

JIB 


ru 

lililllHM 









2 4 6 8 10 12 

Rdavisson/Rcapwap 



gure A-21a Frequency Distribution for All 128 CAPWAP (EOD) Cases 




Ql , : , , , , , , 1 

-0.5 0.5 1 1.5 2 2.5 3 3.5 4 4.5 

Reliability Index, \\ 
Figure A-21b Resistance Factor Calibration from 
128 CAPWAP (EOD) Cases 



205 



10 



4 



2 









1 


! 
























1 i 
























data 

Normal distributic 

Lognormal distrib 


n 

ution 





















































\ 














\ \ 

\ V 


N 












/i 


I 
























\ 

\ 

\ 

X ^ 
X ^ 
X \ 












/ 

y 

y i 
































> 









Rdavisson/Rcapwap 

Figure A-22a Frequency Distribution for 20 CAPWAP-EOD Cases in Florida 




Reliability Index, \\ 
Figure A-22b Resistance Factor Calibration from 
20 CAPWAP-EOD Pile in Florida 



206 



30 



25 




-data 

- Normal distribution 
■ Lognormal distribution 



1.5 2 2.5 3 

Rdavisson/Rcapwap 

Figure A-23a Frequency Distribution for 8 CAPWAP-EOD Cases in California 

2r 




4 5 6 

Reliability Index, \\ 

Figure A-23b Resistance Factor Calibration from 
8 CAPWAP-EOD pile-cases in California 



207 




2 as 3 
Rdavission/Rcapwap 

Figure A-24a Frequency Distribution for 1 1 CAPWAP-EOD Cases in Massachusetts 
1 




2 3 4 5 6 

Reliability Index, \\ 

Figure A-24b Resistance Factor Calibration from 
1 1 CAPWAP-EOD pile-cases in Massachusetts 



208 



2.5 




Rdavission/Rcapwap 

gure A-25a Frequency Distribution for 7 CAPWAP-EOD Cases in Ontario 




Reliability Index, p 
Figure A-25b Resistance Factor Calibration from 
7 CAPWAP-EOD pile-cases in Ontario 



209 



35 



30 



25 



'20 



en 

S3 

e 15 

a. 



10- 







-data 

- Normal distribution 

- Lognormal distribution 




1.8 



0.8 1 1.2 

Rdavission/Rcapwap 

Figure A-26a Frequency Distribution for 9 CAPWAP-EOD Cases in Pittsburgh, PA 

2r 




2 4 
Reliability Index, p 

Figure A-26b Resistance Factor Calibration from 
8 CAPWAP-EOD pile-cases in Pittsburgh, PA 



10 



210 



14 



12 



-data 

■ Normal distribution 
- Lognormal distribution 




2 2.5 3 

Rdavission/Rcapwap 



4.5 



Figure A-27a Frequency Distribution for 8 CAPWAP-EOD Cases in Wisconsin 

2r 




4 5 6 7 

Reliability Index, p 



10 



Figure A-27b Resistance Factor Calibration from 
8 CAPWAP-EOD pile-cases in Wisconsin 



211 



APPENDIX B 
Calibration Resistance Factor by Using FORM 
for Driven Pile using Static Analysis 



25 



20 



J2 
CO 

o 



10 



-data 

- normal distribution 

- log normal distribution 



0.2 



0.4 



0.6 



1.6 



1.8 



0.8 1 1.2 1.4 

RDavisson/RaAPI method 

Figure B-la Frequency Distribution for All 19 
Concrete Pile Cases in Clay by Using aAPI Method 




3 4 

Reliability Index, p 



Figure B-lb Resistance Factor Calibrations from All 
19 Concrete Pile Cases in Clay by Using aAPI Method 



212 




0.5 1 1.5 2 

RDavisson/RoiTomlinson method 

Figure B-2a Frequency Distribution for All 19 
Concrete Pile Cases in Clay by Using aTomlinson Method 




1.5 2 2.5 3 3.5 
Reliability Index, p 

Figure B-2b Resistance Factor Calibration by FORM from All 
19 Concrete Pile Cases in Clay by Using aTomlinson Method 



213 



















1 1 




1 


































data 

normal distribution 

lognormal distribution 










' / 


/ 

/ 


r ' 


r A 


\ 

\ 

I \ 


\ 






j 






// 
// 












■■\ 

\ 

V \ 

\ \ 
\ \ 

— X \ 












A 
/ / 
















V s 













0.2 0.4 0.6 0.8 1 1.2 1.4 1 6 1.8 2 



^Davisson' J^xmethod 

Figure B-3a Frequency Distribution for All 19 
Concrete Pile Cases in Clay by Using \ Method 




0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 



Reliability Index, fi 
Figure B-3b Resistance Factor Calibration from All 
19 Concrete Pile Cases in Clay by Using X Method 



214 



20 
18 
16 
14 
S12 



=10 











































/ 


\\ 




data 


distribution 
al distribution 








/ / 

/ 

/ 

f 


\ N 
\ \ 

\ \ 

V \ 




normal 

log norrr 


1 

|_ 

i 






/ 

/ 

4- 


\ \ 
\ ^ 














i 

_ / / 


1 




\ 

\ 

\ 






f 

u 




/ / 
/ / 






\ \ 

\ \ 
\ \ 






i 


1 n — 






li 
// 






\ \ 
\ \ 
\ \ 










// 

j'-/ 






\\ 
\\ 


- 






f 
















<^ / 














*" ^ 



1,2 1.4 



1,6 



1,8 



0,2 0,4 0.6 0.8 1 

RDavisson/RotAPI method 

Figure B-4a Frequency Distribution for 12 
Concrete Pile Cases in Clay in Louisiana by Using aAPI method 
1 




3 4 5 

Reliability Index, p 



Figure B-4b Resistance Factor Calibration from 
12 Concrete Pile Cases in Clay in Louisiana by Using aAPI method 



215 



18 



16- 




Reliability Index, |1 

Figure B-5b Resistance Factor Calibration from 12 Concrete Pile Cases 
in Clay in Louisiana by Using aXomlinson Method 



216 



30 



25 



5 











































— data 

— normal 

— log norm 


distribution 
si distribut 


ion 










1 ' 


/ 

/ 

/ 

t 




\ 

s 

\ \ 
















} 1 
f / 
/ 

/ 






\ ^ 


\ 

\ 
I \ 
\ \ 












it 
If 
1/ 










\ \ 

\ > 


\ 

L\ 
\\ 












/J 
// 
/ / 























0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 



RDavisson/R)\.rnethod 

Figure B-6a Frequency Distribution for 12 Concrete Pile Cases 
in Clay in Louisiana by Using X Method 




1 2 34 5 6789 10 

Reliability Index, (3 

Figure B-6b Resistance Factor Calibration from 12 

Concrete Pile Cases in Clay in Louisiana by Using \ Method 



217 



14 



12 



data 

Norma! distribution 

Lognorrrjal distribution 




0.5 1 1.5 

RDavisson/RNordlund 

Figure B-7a Frequency Distribution for All 37 
Concrete Pile Cases in Sand by Using Nordlund Method 




2 3 4 

Reliability Index, p 



Figure B-7b Resistance Factor Calibration from all 
37 Concrete Pile Cases in Sand by Using Nordlund Method 



218 



4 









































data 

normal distribution 


































log normal aisiriDuiion 




























\ 


















/ 




(■ 














s 


\ 

\ 


^ 










I / 

1 ^ 
1/ 


/ 
























S 

\ 

V 




















\ 


\ 














1 


































\ 













0.5 1 1.5 2 2.5 3 




Reliability Index, f> 
Figure B-8b Resistance Factor Calibration from all 
37 Concrete Pile Cases in Sand by Using (3 Method 



219 



4 -i, I— 

-data 

- normal distribution 

- log norm a i distribution 



0,2 



0,4 



1,2 



1,4 



0,6 0,8 1 

RDavisson/RlVIeyerhof 

Figure B-9a Frequency Distribution for All 37 
Concrete Pile Cases in Sand by Using Meyerhof 



1,6 



1,8 




1.5 2 
Reliability Index, p 



3.5 



Figure B-9b Resistance Factor Calibration from All 37 
Concrete Piles Cases in Sand by Using Meyerhof Method 



220 




e 0.7 

o 

t3 

s. 
s 

§ 0.5 
'« 

CC 0.4 



0.3 



0.2 



0.1 



1 2 3 4 5 6 

Reliability Index, p 

Figure B-lOb Resistance Factor Calibration for All 

37 Concrete Pile Cases Method in Sand by Using Schmertmann Method 



221 




eo.7 ■ 

a 
tj 

CO 0.6 
II, 

s 

m 

&0A 



0.3 




1 2 3 4 5 6 

Reliability Index, 

Figure B-1 lb Resistance Factor Calibration from 

27 Concrete Pile Cases in Sand in Florida by Using Nordlund Method 



222 


























data 

Normal distribution 

Lognormal distribution 




















































































;v_ 


















• 


















- / 


























Jlk, . 

















































0.5 1 1.5 2 2.5 



RDavisson/Rpmethod 

Figure B-12a Frequency Distribution for 27 
Concrete pile Cases in Sand in Florida by Using p Method 




Reliability Index, p 
Figure B-12b Resistance Factor Calibration from 
27 Concrete Pile Cases in Sand in Florida by Using p Method 



223 



T 1 r- 



T r 



-data 

- Normal distribution 
■ Lognormal distribution 



20 
18 
16 
14 

^ 12 

S 10 

nj 

J3 

6 
4 
2 



0.2 0.4 0.6 0.8 1 1.2 1.4 1 6 1.8 2 

RDavisson/RlVIeyerhof 

Figure B-13a Frequency Distribution for 27 
Concrete Pile Cases in Sand in Florida by Using Meyerhof Method 





1,5 2 2.5 3 3,5 

Reliability Index, \] 

Figure B-13b Resistance Factor Calibration from 

27 Concrete Pile Cases in Sand in Florida by Using Meyerhof Method 



224 















































data 

Normal distribution 

Lognormal distribution 










-- 
















































/' 






\ 














\ S 












I 


/ 

/ 


/ 

f 










'\ 


\ 










it / 


















\ 








/ 


/j 


V 














\ 


\ 

s 





















































0.5 1 1.5 2 2.5 3 



KDavisson' Ksclimeitmann 

Figure B-14a Frequency Distribution for 27 
Concrete Pile Cases in Sand in Florida by Using Schmertmann Method 




■ 1 2 3 4 5 6 7 

Reliability Index, p 

Figure B-14b Resistance Factor Calibration from 
27 Concrete Pile Cases in Sand in Florida by Using Schmertmann Method 



225 



25 



20 



15 



-data 

- normal distribution 

- lognormal distributiorv 




1 1.5 2 

RDavisson/R ctToralinson-Nordlund -Thurraan 

Figure B-15a Frequency Distribution for All 34 Concrete Pile Cases 
in Mixed Soil by Using aTomlinson-Nordlund -Thurman Method 




1 2 3 4 5 6 

Reliability Index, p 

Figure B-15b Resistance Factor Calibration from All 34 Concrete Pile Cases 
in Mixed Soil by Using aXomlinson-Nordlund -Thurman Method 



226 



1 


1 




















































— data 

- normal di 


3tri button 




















— lognormal distribution 


" 
















1 




















- - - 


'-I 














V 

i \ 
\ \ 
\ \ 

.. \ .V 































\ 


\ 










/ 




























,\ 

. s 


- 




n 


n 



0.5 1 1.5 2 2.5 3 3.5 



RDavisson/R aAPI-Nordlund -Thurman 

Figure B-16a Frequency Distribution for all 85 Concrete Pile Cases 
in Mixed Soil by Using aAPI-Nordlund -Thurman Method 




Reliability Index, p 

Figure B-16b Resistance Factor Calibration from All 85 Concrete Pile Cases 
in Mixed Soil by Using R aAPI-Nordlund -Thurman Method 



227 




1 1.5 2 2.5 3 

Rdavisson/R |3-Thurman 
Figure B-17a Frequency Distribution for all 85 Concrete Pile Cases 
in Mixed Soil by Using P-Thurman Method 

0.8 r 




4.5 



2 2.5 3 

Reliability Index, p 

Figure B-17b Resistance Factor Calibration from All 
85 Concrete Pile Cases in Mixed Soil by Using P-Thurman Method 



228 



12 



10- 



data 

— normal distribution 

— log normal distribution 




1 2 3 4 5 6 

RDavisson/R Schmertmann SPT 

Figure B-18a Frequency Distribution for All 74 Concrete Pile Cases 
in Mixed Soil by Using Schmertmann SPT Method 

1 




2.5 3 3.5 4 
Refiability Index, 



5.5 



Figure B-18b Resistance Factor Calibration from all 74 
Concrete Pile Cases in Mixed Soil by Using Schmertmann SPT Method 



229 



16 



14 - 




Reliability Index, p 

Figure B-19b Resistance Factor Calibration from all 32 Concrete Pile Cases 
in Mixed Soil by Using Schmertmann CPT Method 



230 



30 



25 



data 

normal distribution 

— lognormal distribution 




1 1.5 
RDavisson/R aTomlinson-Nordlund -Thurman 

Figure B-20a Frequency Distribution for 12 Concrete Pile Cases 
in Mixed Soil in Florida by Using aTomlinson-Nordlund -Thurman Method 




1.5 2 2.5 3 
Reliability Index, p 



4.5 



Figure B-20b Resistance Factor Calibration from 12 concrete pile cases in mixed soil 
in FL by Using aTomlinson-Nordlund -Thurman Method 



231 



10 
^ 8 

O 
i_ 

O. 

4 











1 


1 
















i 

3 








data 


distribution 
lal distribution 


























normal 

lognorrr 


















1 












\ 


\ 














1 
























\ 


\ 












/ 

/ 

1 

_ / 




























\ 

\ 

\ 

^ \ 












































\ 




" — . . — 









0,5 1 1.5 2 2.5 3 3.5 4 



RDavisson/R aAPI-Nordlund -Thurman 

Figure B-21a Frequency Distribution for 42 Concrete Pile Cases in 
Mixed Soil in Florida by Using aAPI-Nordlund -Thurman 




■ 0,5 1 1.5 2 2.5 3 3.5 4 4.5 5 

Reliability Index, [1 

Figure B-21b Resistance Factor Calibration from 42 Concrete Pile Cases 
in Mixed Soil in Florida by Using aAPI-Nordlund -Thurman 



232 



4 























































al distribution 
rmal distribution 






















- rorm 

— lognc 














































/ 






































y 




















s 








































\ 


\ 

\ 


\ 


\ 


















































\ 

















0.5 1 1.5 2 2.5 3 3.5 4 4.5 



KDavisson' Kp-Xhurman 

Figure B-22a Frequency Distribution for 42 Concrete Pile Cases in 
Mixed Soil in Florida by Using P-Thurman Method 




Reliability Index, [i 

Figure B-22b Resistance Factor Calibration by FORM for 
42 Concrete Pile Cases in Mixed Soil in Florida by Using (3-Thurman Method 



233 




RDavisson/R Schmertmann SPT 

Figure B-23a Frequency Distribution for 55 Concrete Pile Cases in 
Mixed Soil in Florida by Using Schmertmann SPT Method 




5.5 6 



2.5 3 3.5 4 4.5 5 
Reliability Index, p 

Figure B-23b Resistance Factor Calibration from 55 Concrete Pile Cases 
in Mixed Soil in Florida by Using Schmertmann SPT Method 



234 



25 



20 



15 

B 

E 
S 



data 

normal distribution 

lognormal distribution 




0.5 1 1.5 2 

I^Davisson/I^ aTomlinson-Nordlund -Thuraian 

Figure B-24a Frequency Distribution for 16 Concrete Pile Cases in 
Mixed Soil in Louisiana by Using aTomlinson-Nordlund -Thurman Method 
1 




2 3 4 

Reliability Index, p 

Figure B-24b Resistance Factor Calibration from 16 Concrete Pile Cases in Mixed 
soil in Louisiana by Using aTomlinson-Nordlund -Thurman Method 



235 



j3 

















r 


1 

j 

1 

1 




















— data 

— normaldistribution 

— log normal distribution 




1 
1 




















1 

1 




/ 




\ 










J , 


j"""' 

1 

j y 


/ 

I 


/ 

t 






\ 

\ 


\ ...... 












! / 
1/ 


t 










\ 

\ 

\ 












V 





















0,2 0.4 0.6 0.8 1 1,2 1,4 1.6 1.8 




Reliability Index, p 

Figure B-25b Resistance Factor Calibration from 3 1 Concrete pile Cases in Mixed 
Soil in Louisiana by Using aAPI-Nordlund -Thurman Method 



236 



30 



25 



20 



15 



10 



"T 1 r 

I I 



■data 



normal distribution 

log norma I distribution 



0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 

Rdavisson/R (3-Thurman 
Figure B-26a Frequency Distribution for 3 1 Concrete Pile Cases 
in Mixed Soil in Louisiana by Using |3-Thurman Method 




3 4 5 

Reliability Index, p 

Figure B-26b Resistance Factor Calibration by FORM from 3 1 Concrete 
Pile Cases in mixed soil in Louisiana by Using |3-Thurman Method 



237 



20 
18 
16 
14 
^ 12 
1 10 

O 

ol 8 
6 















































c 


ata 

ormal distribution 
M normal distribution 
















r 

1 






























/ 


/ 




\\ 


\ 

\ 














/ 








. \ 
\ \ 
\ \ 










/ 


/ 

/ 










\ \ 






_ 




















■■\' 


\ 

.\... 






/ 


/ 




















\^ 








- / 

/' 






















1 


r ■ 

1 11 - ■ 







0.5 1 1.5 2 2.5 

Rdavisson/R Schmertmann SPT 
Figure B-27a Frequency Distribution for 25 Concrete Pile Cases 
in Mixed Soil in Louisiana by Using Schmertmann SPT Method 
1 




3 4 
Reliability Index, p 

Figure B-27b Resistance Factor Calibration from 25 Concrete Pile Cases in Mixed 
Soil in Louisiana by Using Schmertmann SPT Method 



238 



APPENDIX C 

Calibration Resistance Factor by Using FOSM for Driven Pile 
using CAPWAP Method 



Tab 



e C-1 Total CAPWAP (EOD+BOR) Data 



No. 


Pile-Case 
Number 


Location 


Pile 
Type 


Penetr 


Soil Type 


Davisson's Rdavission 
Criteria (kN) Rcapwap 


oicle 


IIP 


1 
i 


rlN l-tUU 


umana iNt 


rlr 1UX4/ 


1 


silty clay 


4-i 11 
till 


13jZ 


1 Q oo 

1.3ZZ 


Z 


rl\l-r>UKl 


umana iNt 


rlrlUX4/ 


1 QQ 


silty clay 


fill 
till 


i JjZ 


U.oi 1 


'3 
D 


rlN i-r>UK/ 


Omaha NE 


rlrlUX4/ 


oo 

ZZ.Zj 


silty clay 


fill 
till 


toco 
13jZ 


0. /Oj 


A 
4 




umana iNii 


rSiK^lZ sq 


1 Q C 1 


silty clay 


till 
till 


1 coo 

i jyZ 


1 COyI 

i.jo4 


c 

J 


rlNz-JiUK 


umana iNii 


riiK.il sq 


1 Q Q 1 


silty clay 


till 
till 


1 cno 
ij9Z 


1 1 T3 
i.i /3 


D 


T^MT 17/' A FA 


Omaha NE 


roi^i4 sq 


1 /.U / 


silty clay 


till 
till 


i6oi 


Olio 

Z.l iZ 


1 


rlN j-r>UK 


Omaha NE 


roi^i4 sq 


1 /.U / 


silty clay 


till 
till 


1 AO 1 

iooi 


1 0'7'2 
l.Z/j 


Q 

O 


rIN4-ilUU 


umana iNt 


/-"TTPl 'T^" 
i^ilr iz. / J 


on 1 


silty clay 


till 
till 


1 O A Q 

1Z63 


1.164 


Q 

y 




umana iNii 




on 1 


silty clay 


till 
till 


1 OA'2 
iZOJ 


u.yoo 




rlA-ilUU 


Iowa 


rlr 14Xoy 


j4. 


clayey sand 


sand 


4128 


2.529 


1 1 
1 i 


rlA-r>UK 


Iowa 


TTr>l /IvCQ 
rlr i4Xoy 


-54. /o 


clayey sand 


sand 


4128 


1.269 


12 


FIB-EOD 


Iowa 


CEP 14" 


28.68 


clayey sand 


sand 


2891 


1.272 


13 


FIB-BOR 


Iowa 


CEP 14" 


28.68 


clayey sand 


sand 


2891 


1.247 


14 


FOl-EOD 


Oklahoma 


CEP 26" 


18.35 


silty sand 


silty sand 


2660 


1.206 


15 


FOl-BOR 


Oklahoma 


CEP 26" 


18.35 


silty sand 


silty sand 


2660 


0.854 


16 


F02-E0D 


Oklahoma 


PSC24"oct 


19.2 


silty sand 


silty sand 


3381 


1.434 


17 


F02-B0R 


Oklahoma 


PSC24"oct 


19.23 


silty sand 


silty sand 


3381 


1.040 


18 


F03-E0D 


Oklahoma 


HP14xll7 


19.42 


sa-si-clay 


clayey 
sand 


3452 


1.371 


19 


F04-E0D 


Oklahoma 


RC24"sq 


13.72 


sa-si-clay 


clayey 
sand 


7562 


2.584 


20 


F04-BOR 


Oklahoma 


RC24"sq 


17.01 


sa-si-clay 


clayey 
sand 


7562 


2.216 


1 

Zi 






Oregon 


ro^^zu sq 


jo.Zj 


sand & silt 


siltstone 


oUjU 


O /1Q '2 

Z.4-5-5 


ZZ 


rrr^DX not? 


Oregon 


roi^/U sq 


JO.Zo 


sand & silt 


siltstone 




l.ooo 


Zj 


riVlj-ilUU 


Maine 


i^ilr io 


jU. lo 


clay & sand 


sand 


1 Cizn 
lyj 1 


i.Z /Z 


0/1 

Z4 


riVlj-JiUK 


Maine 


i^ilr lo 


1 
jU.Zl 


clay & sand 


sand 


Vyjl 


c\ ooo 
U.ooZ 


Zj 


riVll i-cxjiJ 


Maine 


i^ilr lo 


Zl .0 / 


till 


till 
till 


1 O 1 c 


U.VoZ 


ZD 


riVll /-Jdvjk 


Maine 


l^iir lo 


Zl. / J 


till 

till 


till 
till 


ioi J 


U. / /o 


Z / 


rNVli-cXjU 


Maine 


i^llr lo 


1 J.4j 


till 


till 
till 


1 CO 1 

i jzi 


i.Ujo 


ZS 


rM/j-r>UK 


Maine 


i^llr lo 


1 J.4o 


♦-ill 

till 


till 
till 


i jZi 


l.UUo 


OQ 

ZV 




Colorado 


L-lir i/. / J 


lU.Zi 


sand 


sand 


i4Uo 


1.1/1 






Colorado 


i^llr iz. / J 


lU.jj 


sand 


sand 


1 A rii^ 

i4UD 


1 1 no 

1.19-5 






Colorado 


i^tlr iZ. / J 


o.Uo 


sand 


sand 


1 

IVJ 1 


U.Vol 


jZ 




Colorado 


/^r?pi o T^" 
dir IZ. / J 


O.Z 


sand 


sand 


1 cin 
ioi/ 


l.Uo-5 


J J 


riVlli-iivJU 


Missouri 


l^iir 14 


ZJ.J 


sand-gravel 


sand 


1 /I AO 

i4oo 


1 1 CO 
1.1 JO 


"2/1 


rMll-JiUK 


Missouri 


i^ilr 14 


Zj. JJ 


sand-gravel 


sand 




1 AQ c 


3j 


riVllZ-ilUU 


Missouri 


i^ilr 14 


lo.jV 


sand-gravel 


sand 






JO 


rMlZ-rSUK 


Missouri 


i^iir 14 


1 Q 


sand-gravel 


sand 


930 


0.964 


J / 


V W l\-t-j\J\J 


\Vashingtn 


v^iir 4o 


/ .JO 


till-gravel 


till 


5783 


4.408 


38 


FWA-BOR 


Washingtn 


CEP 48" 


7.59 


till-gravel 


till 


5783 


1.994 


39 


FWB-EOD 


Washingtn 


CEP 48" 


33.22 


till-gravel 


till 


4448 




40 


FWB-BOR 


Washingtn 


CEP 48" 


33.31 


till-gravel 


till 


4448 




41 


FAl-EOD 


Alabama 


PSC 18"sq 


19.51 


silty sand 


silty sand 


1646 


1.805 


42 


FAl-BORl 


Alabama 


PSC 18"sq 


19.66 


silty sand 


silty sand 


1646 


1.440 


43 


FAI-BOR2 


Alabama 


PSC 18"sq 


19.75 


silty sand 


silty sand 


1646 


0.969 



239 



Table C-1 (cont.) 



44 


FA2-EOD 


Alabama 


PSC 18 sq 


22.86 


silty sand 


silty sand 


2447 


1.285 


45 


FA2-BORI 


Alabama 


PSC 18 sq 


22.95 


silty sand 


silty sand 


2447 


1.125 


46 


FA2-BOR2 


Alabama 


PSC 18"sq 


23.01 


silty sand 


silty sand 


2447 


0.919 


47 


FA3-EOD 


Alabama 


PSC 24 sq 


19.51 


silty sand 


silty sand 


2780 


1.839 


48 


FA3-BORI 


Alabama 


PSC 24 sq 


19.54 


silty sand 


silty sand 


2780 


2.035 


49 


FA3-BOR2 


Alabama 


PSC 24 sq 


19.66 


silty sand 


silty sand 


2780 


1.065 


50 


FA4-EOD 


Alabama 


PSC 24 sq 


22.86 


silty sand 


silty sand 


3634 


1.832 


51 


FA4-BOR1 


Alabama 


PSC 24 sq 


22.89 


silty sand 


silty sand 


3634 


1.352 


52 


FA4-BOR2 


Alabama 


PSC 24 sq 


22.92 


silty sand 


silty sand 


3634 


0.959 


53 


FA5-EOD 


Alabama 


PSC 36 sq 


22.25 


silty sand 


silty sand 


5071 


1.722 


54 


FA5-BOR 


Alabama 


PSC 36"sq 


22.28 


silty sand 


silty sand 


5071 


1.206 


55 


FV15-EOD 


Vermont 


HP 14x7 3 


22.86 


silt-d.sand 


sand gravel 


1401 


1.623 


56 


FV15-BOR 


Vermont 


T Tl~* t A 

HP 14x7 3 


23.1 


silt-d.sand 


sand gravel 


1401 


1.590 


57 


FVIO-EOD 


Vermont 


T TT* A A 

HP 14x7 3 


27.43 


silt-d.sand 


sand gravel 


1535 


2.171 


58 


FVIO-BOR 


Vermont 


HP 14x7 3 


27.55 


silt-d.sand 


sand gravel 


1535 


1.928 


59 


FMN2-EOD 


Minnesota 


HP 14x7 3 


29.26 


sa-si-clay 


fat clay 


3403 


2.237 


60 


FMN2-BOR 


Minnesota 


HP 14x7 3 


29.29 


sa-si-clay 


fat clay 


3403 


1.173 


61 


FP5-EOD 


Penn. 


Monotube 


7.19 


sandy grvl 


sandy grvl 


1081 


1.157 


62 


FP5-BOR 


Penn. 


Monotube 


7.25 


sandy grvl 


sandy grvl 


1081 


1.017 


63 


FKG-EOD 


Kentucky 


PSC14"sq 


10.58 


soft clay 


dense 


1628 


1.271 


64 


FKG-BOR 


Kentucky 


PSC14"sq 


10.58 


soft clay 


dense 


1628 


1.241 


65 


FL3-EOD 


Louisiana 


7~»r^ /"li^ A IT 

PSC24 sq 


25.69 


silty clay 


silty sand 


1779 


2.940 


66 


FL3-BORI 


Louisiana 


PSC 24 sq 


25.69 


silty clay 


silty sand 


1779 


1.470 


67 


FL3-BOR2 


Louisiana 


PSC24 sq 


25.69 


silty clay 


silty sand 


1779 


1.143 


68 


CAI-EOD 


O.S. Ont 


CEP 9.6" 


47.03 


si-sa-clay 


si-sa-till 


2402 


1.317 


69 


CAl-BOR 


O.S. Ont 


CEP 9.6" 


47.03 


si-sa-clay 


si-sa-till 


2402 


1.080 


70 


CA2-BOR 


O.S. Ont 


CEP 9.6" 


33.56 


si-sa-clay 


si-sa-clay 


1628 


1.070 


71 


CA5-BORI 


N.Y. Ont 


CEP11.73 


19.26 


fill-sand 


sand 


2082 


1.145 


72 


CA5-BOR2 


N.Y. Ont 


CEP11.73 


19.99 


fill-sand 


sand 


2082 


0.957 


73 


CA3/8-BOR 


Bar. Ont 


CEP 10. 24 


19.63 


sand-silt 


silt 


841 


0.785 


74 


CA24-BOR 


Tor. Ont 


/~1T^7~*1 1^ TriT 

CEP12.75 


11.77 


sand 


sand 


1076 


1.168 


75 


CA6-BOR1 


Ham. Ont 


/~1T^7~»1 1^ ^^11 

CEP12.75 


16.46 


sa-si-till 


silt-till 


2936 


1.082 


76 


CA6-BOR2 


Ham. Ont 


/~1T^7~»1 1^ ^^11 

CEP12.75 


16.46 


sa-si-till 


silt-till 


2936 


1.130 


77 


CA6-EOR 


Ham. Ont 


/~1T^T»1 1^ TriT 

CEP12.75 


16.46 


sa-si-till 


silt-till 


2936 


1.183 


78 


WC3-EOD 


Florida 


T~\r^ /^i^ A IT 

PSC24 sq 


8.32 


Is. -d. sand 


dense 


2713 


1.198 


79 


WC3-BORI 


Florida 


PSC24 sq 


8.38 


Is. -d. sand 


dense 


2713 


1.205 


80 


WC3-BOR2 


Florida 


7~*P1 /^i^ A IT 

PSC24 sq 


8.38 


Is: d.sand 


dense 


2713 


1.138 


81 


WC6-EOD 


Florida 


7~»T1 /^i^ -1 IT 

PSC24 sq 


8.63 


Is.-dsand 


dense 


2015 


1.006 


82 


WC6-BOR1 


Florida 


PSC24 sq 


8.69 


Is. -d.sand 


dense 


2015 


0.944 


83 


WC6-BOR2 


Florida 


PSC24 sq 


8.38 


Is. -d.sand 


dense 


2015 


1.022 


84 


WB9-BOR 


Florida 


PSC30 sq 


39.17 


clayey sand 


clayey 


4003 


0.956 


o c 
5J 


WBlj-BUR 


Florida 


riiC30 sq 


31. JO 


sand 


silt-clay 


364o 


1.019 


86 


Tl/A-EOD 


Israel 


OEP 60" 


16.09 


clcr sand 


sand 


8825 


1.118 


87 


Tl/A-ALT 


Israel 


OEP 60" 


16.4 


cler sand 


sand 


8825 


1.102 


88 


TIB-EOD 


Israel 


OEP 60" 


31 


clcr sand 


sand 


12749 


1.211 


89 


T2/A-EOD 


Israel 


OEP 48" 


16 


cler sand 


sand 


5983 


1.074 


90 


T2/B-EOD 


Israel 


OEP 48" 


55.5 


clcr sand 


sand 


14612 


1.182 


91 


35-1-BOR 


Toronto 


HP12x74 


14.78 


cl-sa-silt 


silty sand 


1432 


1.238 



240 



Table C-1 (cont.) 



92 


35-4-BOR 


Toronto 


CEP12.75 


14.69 


cl-sa-silt 


silty sand 


1468 


0.917 


93 


35-5-BOR 


Toronto 


HP 12x74 


27.58 


cl-sa-silt 


silty sand 


2722 


0.942 


94 


35-6-BOR 


Toronto 


CEP12.75 


27.43 


cl-sa-silt 


silty sand 


2669 


1.034 


95 


35-7-BOR 


Toronto 


T. Timber 


12.68 


cl-sa-silt 


silty sand 


543 


0.879 


96 


35-10-BOR 


Toronto 


PSC 12"sq 


14.63 


cl-sa-silt 


silty sand 


1788 


1.203 


97 


E2-BOR 


Raleigh 


PSC 12 sq 


13.56 


cl-sa-silt 


cl-sa-silt 


1846 


0.988 


98 


63S-BOR 


Penn. 


HP 12x5 3 


20.12 


sand-silt 


silt 


1263 


1.018 


99 


LB21-BOR 


NA 


PSC 20 sq 


10.97 


silt-sand 


silt-sand 


1690 


1.052 


100 


LB20-BOR 


NA 


PSC 20 sq 


16.76 


sand 


sand 


2580 


1.224 


101 


LC3-BOR 


NA 


PSC 20 sq 


26.21 


cl-sa-silt 


cl-sa-silt 


2758 


1.013 


102 


L1N16-BOR 


NA 


PSC 20 sq 


28.65 


cl-sa-silt 


cl-sa-silt 


2669 


1.031 


103 


LE37-BOR 


NA 


PSC 10 sq 


15.24 


cl-sa-silt 


limestone 


1112 


1.269 


104 


LE64-BOR 


NA 


PSC 10"sq 


17.68 


cl-sa-silt 


sa-cl-silt 


1201 


1.164 


105 


STl-EOD 


Florida 


PSC 18"sq 


13.41 




carb sand 


1530 


0.681 


106 


ST2-EOD 


Florida 


PSC 18 sq 


12.19 




carb sand 


2269 


0.828 


107 


ST9-BOR 


Virginia 


PSC 54 sq 


33.22 




silt-clay 


4092 


1.140 


108 


ST46-EOD 


New York 


CEP 10" 


11.58 


silt-sand 


silt-sand 






109 


GZA3-EOD 


Prov. RI 


CEP13.38 


38.25 


silt-sand 


gr-sa-silt 


1957 


1.205 


110 


GZA5-EOD 


Prov. RI 


CEP 9.75 


28.59 


silt-sand 


till-shale 


1139 


0.874 


111 


GZA6-EOD 


Prov. RI 


CEP 9.75 


47.55 


silt-sand 


gr-sa-silt 


836 


0.684 


112 


GZBBC-EOD 


Prov. RI 


CEP 10" 


30.33 


silt-sand 


silt 


1957 


1.065 


113 


GZBP2-EOD 


Prov. RI 


CEP13.38 


32.31 


silt-sand 


gr-sa-silt 


1246 


0.884 


1 14 


GZB6-EOD 


Prov. RI 


CEP13.38 


28.13 


silt-sand 


si-sa-till 


1690 


1.114 


115 


GZZ5-EOD 


Boston MA 


CEP 14" 


26.52 


till-clay 


till 


2064 


2.168 


116 


GZ05-E0D 


Boston MA 


CEP 14" 


16.46 


till-clay 


till 


2135 


2.341 


117 


GZCC5-EOD 


Boston MA 


CEP 14" 


24.38 


till-clay 


till 


2002 


0.915 


118 


GZL2-EOD 


Boston MA 


CEP 14 


25.3 


till-clay 


till 


2847 


2.396 


119 


GZP14-EOD 


Boston MA 


CEP 14 


18.44 


till-clay 


till 


1735 


1.279 


120 


GZPU-EOD 


Boston MA 


CEP 14" 


17.22 


till-clay 


till 


1112 


1.046 


121 


GZP12-EOD 


Boston MA 


/—I T~i 1 /I II 

CEP 14 


21.03 


till-clay 


till 


2224 


0.962 


122 


GZB22-EOD 


Colt Neck 


OEP 36 


35.97 


sand-clay 


silt-clay 


4982 


1.010 


123 


GZW 1-EOR 


Vermont 


CP12.75 


30.33 


silty sand 


sand 


1601 


1.440 


124 


A54-EOD 


Australia 


RC10.8"sq 


20.6 


silty clay 


clay 


2900 


1.702 


125 


A54-BOR 


Australia 


RC10.8 sq 


20.6 


silty clay 


clay 


2900 


1.067 


126 


A147-EOD 


Australia 


RCI0.8"sq 


20.6 


silty clay 


clay 


2482 


2.155 


127 


A 1 /I O 1~A A A TA 

A147-BOR 


Australia 


RC10.8"sq 


20.6 


silty clay 


clay 


2482 


0.989 


128 


GF19-EOD 


Pgh. PA 


HP10x42 


15.09 


grvl-snd-slt 


shale 


1468 


0.829 


129 


GFl 10-EOD 


Pgh. PA 


HP 12x74 


15.15 


grvl-snd-slt 


shale 


2224 


1.094 


130 


GF222-EOD 


Pgh. PA 


HP 12x74 


18.62 


grvl-snd-slt 


shale 


2580 


1.133 


131 


GF224-EOD 


Pgh. PA 


Monotube 


9.02 


grvl-snd-slt 


grvl-snd-slt 






132 


GF312-EOD 


Pgh. PA 


HP 12x74 


8.6 


snd-grvl-shl 


shale 


1512 


0.839 


133 


Gr313-bUD 


rgh. rA 


HrlOxj / 


9.6 


snd-grvl-shl 


claystone 


1456 


0. /49 


134 


GF412-EOD 


Pgh. PA 


HP 12x74 


10.24 


grvl-snd-slt 


claystone 


1068 


0.528 


135 


GF413-EOD 


Pgh. PA 


HP 10x57 


10.55 


grvl-snd-slt 


claystone 


1334 


0.701 


136 


GF414-EOD 


Pgh. PA 


HPIOx57 


10.58 


grvl-snd-slt 


claystone 


1601 


0.687 


137 


GF415-EOD 


Pgh. PA 


HP 12x74 


10.39 


grvl-snd-slt 


claystone 


2046 


0.820 


138 


EF62-EOD 


Canada 


CP 9.625" 


18.99 


si-sa-clay 


till 


2233 


0.962 


139 


EF167-BOR 


Canada 


CP 9.625" 


21 


si-sa-clay 


till 


1205 


0.565 



241 



Table C-1 (cont.) 



140 


A3-EOD2 


Florida 


VC 24"sq 


27.52 


clayey sand 


sand 


4261 


2.603 


141 


A3-BOR2 


Florida 


VC 24"sq 


27.55 


clayey sand 


sand 


4261 


2.073 


142 


A3-BOR3 


Florida 


VC 24"sq 


27.61 


clayey sand 


clayey sand 


4261 


1.035 


143 


A14-DD1 


Florida 


VC 24"sq 


13.72 


sandy clay 


sand 






144 


A14-DD2 


Florida 


VC 24"sq 


14.33 


sandy clay 


sand 






145 


A14-BOR1 


Florida 


VC 24"sq 


17.83 


clayey sand 


sand 






146 


A14-BOR2 


Florida 


VC 24"sq 


17.92 


clayey sand 


sand 






147 


A25-EOD 


Florida 


VC 24"sq 


16.79 


clayey sand 


sand 


3180 


1.557 


148 


A25-BOR1 


Florida 


VC 24"sq 


16.82 


clayey sand 


sand 


3180 


1.288 


149 


A25-BOR2 


Florida 


VC 24"sq 


16.89 


clayey sand 


sand 


3180 


1.581 


150 


A25-BOR3 


Florida 


VC 24"sq 


16.92 


clayey sand 


sand 


3180 


1.617 


151 


AI6-EOD 


Florida 


PSC18"sq 


18.47 


sandy clay 


sand 


1401 


1.407 


152 


A16-BOR1 


Florida 


PSC18 sq 


18.47 


sandy clay 


sand 


1401 


1.117 


153 


A16-BOR2 


Florida 


PSC18 sq 


18.59 


sandy clay 


sand 


1401 


1.064 


154 


AAA 1 — V 

A41-EOD 


Florida 


VC 24"sq 


15.85 


clay 


sand 


2331 


1.216 


155 


\ A A /^T* A 

A41-BOR1 


Florida 


VC 24"sq 


15.85 


clay 


sand 


2331 


1.042 


156 


A41-BOR2 


Florida 


VC 24"sq 


16.09 


clay 


sand 


2331 


0.928 


157 


AlOl-EOD 


Florida 


VC 24"sq 


18.84 


clay 


clayey sand 


3612 


1.570 


158 


AlOl-BORI 


Florida 


VC 24"sq 


18.84 


clay 


clayey sand 


3612 


1.214 


159 


A101-BOR2 


Florida 


VC 24"sq 


18.93 


clay 


clayey sand 


3612 


1.011 


160 


A133-EOD 


Florida 


VC 24"sq 


31.67 


clayey sand 


sandy clay 


3594 


2.599 


161 


A133-BOR 


Florida 


VC 24"sq 


31.97 


clayey sand 


sandy clay 


3594 


1.036 


162 


A145-EOD 


Florida 


VC 24"sq 


31.36 


clayey sand 


sand 


4341 


2.765 


163 


A145-BOR1 


Florida 


VC 24"sq 


31.36 


clayey sand 


sand 


4341 


1.523 


164 


A145-BOR2 


Florida 


VC 24"sq 


31.39 


clayey sand 


sand 


4341 


1.282 


165 


CB3-BOR 


Florida 


PSC24 sq 


23.47 


clayey sand 


sand 


2224 


0.886 


166 


CB3-BORL 


Florida 


PSC24 sq 


23.71 


clayey sand 


sand 


2224 


0.996 


167 


CB5-BOR 


Florida 


VC 30"sq 


16.18 


clayey sand 


sand 


5560 


2.200 


168 


CB5-BORL 


Florida 


VC 30"sq 


16.46 


clayey sand 


sandy clay 


5560 


2.140 


169 


CBl 1-BORL 


Florida 


VC 30"sq 


26.12 


clayey sand 


clayey sand 


6383 


1.763 


170 


CBll-EORL 


Florida 


VC 30"sq 


26.15 


clayey sand 


clayey sand 


6383 


2.246 


171 


CB17-BOR1 


Florida 


VC 30"sq 


23.68 


clayey sand 


clayey sand 


6739 


1.847 


172 


CB17-BOR2 


Florida 


VC 30"sq 


23.71 


clayey sand 


clayey sand 


6739 


2.023 


173 


CB17-BORL 


Florida 


VC 30"sq 


23.74 


clayey sand 


clayey sand 


6739 


2.218 


174 


CB17-DRL 


Florida 


VC 30"sq 


23.84 


clayey sand 


clayey sand 


6739 


1.793 


175 


CB23-BOR 


Florida 


VC 30"sq 


24.48 


clayey sand 


sand 


2860 


1.039 


176 


CB23-BORE 


Florida 


VC30"sq 


25.21 


clayey sand 


sand 


2860 


1.448 


177 


CB29-BORL 


Florida 


VC 30"sq 


25.76 


clayey sand 


clayey sand 


4079 


1.182 


178 


CB29-EORL 


Florida 


VC 30"sq 


25.76 


clayey sand 


clayey sand 


4079 


2.043 


179 


CB35-BOR1 


Florida 


VC 30"sq 


23.93 


clayey sand 


clayey sand 


6508 


1.802 


180 


CB35-BOR2 


Florida 


VC 30"sq 


24.05 


clayey sand 


clayey sand 


6508 


1.542 


1 O 1 

lol 


L,B3j-BURL 


Florida 


VC 30 sq 


24. 1 1 


clayey sand 


clayey sand 


6j0o 


1 1 r\ 
1.610 


182 


CB41-EOR 


Florida 


VC 30"sq 


19.72 


sandy clay 


sandy clay 


6272 


1.645 


183 


CB41-BOR 


Florida 


VC 30"sq 


19.72 


sandy clay 


sandy clay 


6272 


1.659 


184 


CB4 1-BORL 


Florida 


VC 30"sq 


19.93 


sandy clay 


sandy clay 


6272 


2.908 


185 


CB26-EOD 


Florida 


PSC24"sq 


19.05 


clayey sand 


sand 


4270 


1.967 


186 


CB26-BOR 


Florida 


PSC24"sq 


19.08 


clayey sand 


sand 


4270 


1.551 


187 


CB26-EOR 


Florida 


PSC24"sq 


19.75 


clayey sand 


sandy clay 


4270 


1.341 



242 



Table C-1 (cont.) 



188 


CB26-BOR2 


Florida 


PSC24 sq 


19.81 


sandy clay 


sandy clay 


4270 


1.705 


189 


33P1-EOD 


Ontario 


T Tr* 1 il 1^ A 

HP 12x74 


34.87 


cl-sa-silt 


silty sand 


3559 


1.822 


190 


33P1-BOR 


Ontario 


HP 12x74 


34.87 


cl-sa-silt 


silty sand 


3559 


1.119 


191 


33P1-EOR 


Ontario 


T Tl~* 1 il A 

HP 12x74 


34.87 


cl-sa-silt 


silty sand 


3559 


1.231 


192 


33P2-EOD 


Ontario 


CP 12.75 


32.67 


cl-sa-silt 


silty sand 


2180 


1.690 


193 


33P2-BOR 


Ontario 


CP 12.75 


32.67 


cl-sa-silt 


silty sand 


2180 


1.381 


194 


33P2-EOR 


Ontario 


CP 12.75 


32.67 


cl-sa-silt 


silty sand 


2180 


1.222 


195 


33P4-EOD 


Ontario 


"r^c 1 ii ti 

PSC 12 sq 


16.52 


cl-sa-silt 


cl-silt-till 


2073 


1.165 


196 


33P5-EOD 


Ontario 


#14 Timber 


8.66 


cl-sa-silt 


cl-silt-till 


730 


1.148 


197 


TRD22-EOD 


Ontario 


T Tr* 1 il T -t 

HP 12x74 


6.13 


sand 


till 


1575 


0.819 


198 


TRD22-BOR 


Ontario 


HP 12x74 


6.13 


sand 


till 


1575 


1.204 


199 


TRE22-EOD 


Ontario 


T Tr* 1 ii ^ /I 

HP 12x74 


7.83 


sand 


rock 


2473 


0.967 


200 


TRE22-BOR 


Ontario 


HP 12x74 


7.83 


sand 


rock 


2473 


0.903 


201 


TRP5X-EOD 


Ontario 


T Tr* 1 ii n 

HP 12x53 


7.68 


sand 


rock 


1824 


0.847 


202 


TRP5X-BOR 


Ontario 


T Tr* 1 ii n 

HP 12x53 


7.68 


sand 


rock 


1824 


1.038 


203 


TR131-BOR 


Ontario 


CP 7.063 


NA 


sand 


rock 


623 


0.844 


204 


'T'T^ ATT T^" 

TRAH-EOR 


Brunswick 


T T7~» 1 il C\ 

HP 12x89 


38.4 


clayey silt 


sandy gravel 


3247 


3.347 


205 


TRBH-BOR 


Brunswick 


HP 12x89 


31.12 


clayey silt 


sandy gravel 


1446 


3.249 


206 


TRBP-EOR 


Brunswick 


CP 12.75 


31.7 


clayey silt 


sandy gravel 


1512 


1.371 


207 


CHAT-EOD 


Wisconsin 


CEP 12.75 


37.49 


sa-si clay 


silty sand 


2909 


1.677 


208 


CHAT-BORl 


Wisconsin 


CEP 12.75 


37.52 


sa-si clay 


silty sand 


2909 


1.407 


209 


CHA1-BOR2 


Wisconsin 


CEP 12.75" 


37.52 


sa-si clay 


silty sand 


2909 


1.263 


210 


CHA4-EOD 


Wisconsin 


CEP 12.75" 


35.66 


sa-si clay 


silty sand 


2251 


1.868 


211 


CHB2-EOD 


Wisconsin 


HP12x63 


47.34 


sa-si clay 


silty sand 


1343 


2.746 


212 


CHB2-BOR1 


Wisconsin 


HP12x63 


47.34 


sa-si clay 


silty sand 


1343 


1.118 


213 


CHB2-BOR3 


Wisconsin 


HP12x63 


47.4 


sa-si clay 


silty sand 


1343 


0.888 


214 


CHB2-BOR4 


Wisconsin 


HP12x63 


47.43 


sa-si clay 


silty sand 


1343 


0.671 


215 


CHB2- 
BOR5a 


Wisconsin 


HP12x63 


47.46 


sa-si clay 


silty sand 


1343 


0.586 


216 


CHB2- 
BOR5b 


Wisconsin 


HP12x63 


47.46 


sa-si clay 


silty sand 


1343 


0.632 


217 


CHB3-EOD 


Wisconsin 


T TT» 1 il 1 

HP 12x63 


43.31 


sa-si clay 


silty sand 


890 


1.906 


218 


CHB3-BOR1 


Wisconsin 


T T7~» 1 il 1 

HP 12x63 


43.31 


sa-si clay 


silty sand 


890 


0.852 


219 


CHB3-BOR2 


Wisconsin 


HP 12x63 


43.43 


sa-si clay 


silty sand 


890 


0.909 


220 


CHB3-BOR3 


Wisconsin 


T Tl~* 1 il /'I 

HP 12x63 


43.53 


sa-si clay 


silty sand 


890 


0.597 


221 


/^TT/^1 T^/^T^ 

CHC3-EOD 


Wisconsin 


CEP14" 


47.3 


sa-si clay 


silty sand 


836 


1.710 


222 


/^TT/^1 T"* 

CHC3-BOR 


Wisconsin 


CEP14" 


47.3 


sa-si clay 


silty sand 


836 




223 


CHC3-BORL 


Wisconsin 


CEP14" 


47.34 


sa-si clay 


silty sand 


836 


0.482 


224 


CH4-EOD 


Wisconsin 


CEP9.63" 


43.43 


silty clay 




1601 


2.400 


225 


CH4-BOR 


Wisconsin 


CEP9.63" 


43.43 


silty clay 




1601 


1.059 


226 


CH39-EOD 


Wisconsin 


CEP9.63" 


43.28 


silty clay 


silty clay 


2936 


3.529 


227 


CH39-BOR 


Wisconsin 


CEP9.63 


43.28 


silty clay 


silty clay 


2936 


1.435 


228 


CH39-BORL 


Wisconsin 


CEP9.63" 


43.37 


silty clay 


silty clay 


2936 


1.148 


229 


CH6-5B- 
EOD 


Wisconsin 


CEP9.63" 


43.89 


silty clay 


silty sand 


1673 




230 


CH6-5B- 
BOR 


Wisconsin 


CEP9.63" 


43.89 


silty clay 


silty sand 


1673 


0.940 


231 


CH95B-EOD 


Wisconsin 


CEP9.63" 


42.37 


silty clay 


sand & 
grvl 


2473 


2.516 



243 



Table C-1 (cont.) 



232 


CH95B-BOR 


Wisconsin 


CEP9.63" 


42.37 


silty clay 


sand & 
grvl 


2473 


1.049 


233 


CH256- 
BOR3 


Wisconsin 


CEP9.63" 


42.67 


si-sa clay 


si-sa & 
grvl 


2651 


1.192 


234 


CH351- 
BOR2 


Wisconsin 


CEP9.63" 


47.55 


si-sa clay 


si-sa & 
grvl 


2669 


1.132 


235 


P02-B0R1 


Florida 


PSC18"sq 


5.73 


sand 


dense sand 


1219 


0.902 


236 


P02-BOR2 


Florida 


PSC18 sq 


6.07 


sand 


dense sand 


1219 


1.038 


237 


P02-B0RL 


Florida 


PSC18"sq 


6.28 


sand 


dense sand 


1219 


0.975 


238 


P019-B0R 


Florida 


PSC18"sq 


4.63 


sand 


dense sand 


1023 


0.767 


239 


P019-E0D 


Florida 


PSC18"sq 


5.24 


sand 


dense sand 


1023 


0.939 


240 


P019-E0RL 


Florida 


PSC18"sq 


5.36 


sand 


dense sand 


1023 


0.979 


241 


ER5-BOR1 


Florida 


PSC24 sq 


25.97 


sand 


sand 


3803 


1.299 


242 


ER5-BOR2 


Florida 


PSC24 sq 


26.03 


sand 


sand 


3803 


0.922 


243 


ER5-BORL 


Florida 


PSC24"sq 


26.15 


sand 


sand 


3803 


1.457 


244 


ER77-BOR 


Florida 


PSC24"sq 


18.56 


clayey sand 


cl-si-sand 


7433 


2.210 


245 


ER77-BORL 


Florida 


PSC24"sq 


18.68 


clayey sand 


cl-si-sand 


7433 


1.658 


246 


BB13-EOD 


Florida 


VC 30"sq 


28.29 


clayey sand 


sand 


4475 


1.437 


247 


BB13-BORla 


Florida 


VC 30"sq 


28.32 


clayey sand 


sand 


4475 


1.094 


248 


BB13-BORIb 


Florida 


VC 30"sq 


28.32 


clayey sand 


sand 


4475 


1.130 


249 


BB 13- 
BOR2a 


Florida 


VC 30"sq 


28.71 


clayey sand 


sand 


4475 


0.940 


250 


BB13-BOR2b 


Florida 


VC 30"sq 


28.71 


clayey sand 


sand 


4475 


0.958 


251 


BB I3-BORL 


Florida 


VC 30"sq 


28.8 


clayey sand 


sand 


4475 


1.117 


252 


BB19-BORa 


Florida 


VC 30"sq 


27.13 


sand 


sand 


5169 


1.244 


253 


BB19-BORb 


Florida 


VC 30"sq 


27.13 


sand 


sand 


5169 


1.108 


254 


BB19-BORL 


Florida 


VC 30"sq 


27.19 


sand 


sand 


5169 


0.794 


255 


BB24-EOD 


Florida 


VC 30"sq 


24.44 


sand 


clay 


4955 


0.857 


256 


BB24-BORla 


Florida 


VC 30"sq 


24.48 


sand 


clay 


4955 


0.659 


257 


BB24-BORIb 


Florida 


VC 30"sq 


24.48 


sand 


clay 


4955 


0.654 


258 


BB24-BOR2a 


Florida 


VC 30"sq 


24.63 


sand 


clay 


4955 


0.588 


259 


131324- 
BOR2b 


Florida 


VC 30"sq 


24.63 


sand 


clay 


4955 


0.629 


260 


BB24-BORL 


Florida 


VC 30"sq 


24.69 


sand 


clay 


4955 


0.794 


261 


BB29-BOR 


Florida 


VC 30"sq 


23.90 - 


sand 


sand 


5053 


0.926 


262 


BB29-BORL 


Florida 


VC 30"sq 


23.96 


sand 


sand 


5053 


0.988 


263 


ABF6-BOR 


Florida 


PSC 24" sq 


17.54 


si/clayey sand 


clayey 
sand 


3345 


1.995 


264 


ABF6-BORL 


Florida 


PSC 24" sq 


17.84 


si/clayey sand 


clayey 
sand 


3345 


0.963 


265 


ABG13- 
BORL 


Florida 


PSC 24" sq 


14.08 


clayey sand 


limestone 


4742 


0.983 


zoo 


ABHz-BOR 


Flonda 


PSC 24 sq 


10.9 


silt/silty clay 


limestone 


2518 


0.701 


267 


ABH2-BORL 


Florida 


PSC 24" sq 


10.96 


silt/silty clay 


limestone 


2518 


0.615 


268 


BC79-EOD 


S.Carolina 


PSC 24" oct 


23.47 


si-cl-sand 


calcar sand 


2277 




269 


BC79-BORL 


S.Carolina 


PSC 24" oct 


23.5 


si-cl-sand 


calcar sand 


2277 


0.931 


270 


BC64-EOD 


S.Carolina 


PSC 24" oct 


18.59 


si-cl-sand 


calcar sand 


5071 




271 


BC64-BORL 


S.Carolina 


PSC 24" oct 


18.62 


si-cl-sand 


calcar sand 


5071 


1.013 


272 


DI-BORI 


Holland 


PSC 9.7"sq 


10.91 


clay-sand 


sand 


302 


0.714 



244 



Table C-1 (cont.) 



273 


D2-BOR1 


Holland 


PSC 9.7 sq 


14.3 


clay-sand 


clay 


556 


0.850 


274 


D3-BORa 


Holland 


PSC 9.7 sq 


18.29 


clay-sand 


sand 


1005 


1.229 


275 


D3-BORb 


Holland 


7~*0/^ r\ TIT 

PSC 9.7 sq 


18.29 


clay-sand 


sand 


1005 


1.448 


276 


D5-BORa 


Holland 


PSC 9.7 sq 


18.29 


clay-sand 


sand 


1050 


0.787 


277 


D5-BORb 


Holland 


7~»r^ /~i r\ TIT 

PSC 9.7 sq 


18.29 


clay-sand 


sand 


1050 


0.797 


278 


MB 1 -EOD 


S. Carolina 


PSC 16"sq 


18.9 


sand 


silty sand 


3590 


4.749 


279 


MBl-BOR 


S. Carolina 


PSC 16"sq 


19.2 


sand 


silty sand 


3590 


1.543 


280 


MB2-BOR 


S. Carolina 


HP 14x89 


20.12 


silty sand 


calcar. silt 


3990 


1.689 


281 


MB3-BOR 


S. Carolina 


OEP 16" 


20.12 


silty sand 


calcar. silt 


4146 


1.632 


282 


SI -EOD 


S. Carolina 


OEP 24" 


24.84 


clayey sand 


sandy silt 


2651 


1.296 


283 


SI-BOR 


S. Carolina 


OEP 24 


24.84 


clayey sand 


sandy silt 


2651 


0.987 


284 


S2-EOD 


S. Carolina 


HP14x73 


23.77 


clayey sand 


sandy silt 


1415 


1.480 


285 


S2-BOR 


S. Carolina 


HP14x73 


23.77 


clayey sand 


sandy silt 


1415 


1.036 


286 


DD22-EOD 


Florida 


PSC 14"sq 


27.43 


clay 


sand 


3745 


3.302 


287 


DD22-BOR 


Florida 


PSC 14"sq 


27.74 


clay 


sand 


3745 


1.622 


288 


DD23-EOD 


Florida 


CEP 12.75 


24.99 


clay 


sand 


2206 


3.239 


289 


DD23-BOR 


Florida 


CEP 12.75 


25.09 


clay 


sand 


2206 


1.791 


290 


JR17-EOD 


Richmond, 
VA 


PSC 24" sq 


10.76 


cl-si-sand 


silty sand 


5422 


1.947 


291 


LB 3 -EOD 


Kenner, LA 


PSC 24 sq 


24.84 


clay 


Sand 


1842 


6.848 


292 


LB3-BOR1 


Kenner, LA 


PSC 24 sq 


24.99 


clay 


Sand 


1842 


2.020 


293 


LB3-BOR2 


Kenner, LA 


PSC 24 sq 


24.99 


clay 


Sand 


1842 


1.201 


294 


LB3-BOR3 


Kenner, LA 


PSC 24 sq 


24.99 


clay 


Sand 


1842 


1.098 


295 


LB4-EOD 


Kenner, LA 


PSC 30 sq 


24.99 


clay 


Sand 


2273 


11.252 


296 


LB4-BOR1 


Kenner, LA 


PSC 30 sq 


25.21 


clay 


Sand 


2273 


2.563 


297 


LB4-BOR2 


Kenner, LA 


PSC 30 sq 


25.27 


clay 


Sand 


2273 


1.750 


298 


LB4-BOR3 


Kenner, LA 


PSC 30 sq 


25.3 


clay 


Sand 


2273 


1.494 


299 


LB4-BOR4 


Kenner, LA 


PSC 30 sq 


25.3 


clay 


Sand 


2273 


1.418 


300 


LB5-EOD 


Kenner, LA 


PSC 30 sq 


24.99 


clay 


Sand 






301 


LB5-BOR1 


Kenner, LA 


PSC 30 sq 


24.99 


clay 


Sand 






302 


LB5-BOR2 


Kenner, LA 


PSC 30 sq 


24.99 


clay 


Sand 






303 


LB5-BOR3 


Kenner, LA 


PSC 30 sq 


25.3 


clay 


Sand 






304 


LB5-BOR4 


Kenner, LA 


PSC 30 sq 


25.3 


clay 


Sand 






305 


LB6-EOD 


Kenner, LA 


PSC 36 cyl 


24.69 


clay 


Sand 


2411 


5.968 


306 


LB6-BOR1 


Kenner, LA 


PSC 36 cyl 


24.69 


clay 


Sand 


2411 


2.730 


307 


LB6-BOR2 


Kenner, LA 


PSC 36 cyl 


24.69 


clay 


Sand 


2411 


1.824 


308 


LB6-BOR3 


Kenner, LA 


PSC 36 cyl 


24.99 


clay 


Sand 


241 1 


1.364 


309 


LB6-BOR4 


Kenner, LA 


PSC 36" cyl 


24.99 


clay 


Sand 


2411 


1.048 


310 


LB7-EOD 


Kenner, LA 


PSC 36" cyl 


24.6 


clay 


Sand 


2402 


5.256 


311 


LB7-BOR1 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


2.745 


312 


LB7-BOR2 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


1.878 


313 


LB7-BOR3 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


1.270 


314 


LB7-BOR4 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


1.063 


315 


DI221-EOD 


Massachusetts 


PSC 14" sq 


19.2 


sa-si-clay 


fine sand & 
silt 


1477 




316 


DI221-2DR 


Massachusetts 


PSC 14" sq 


19.2 


sa-si-clay 


fine sand & 
silt 


1477 


1.182 


317 


TW488-EOD 


Massachusetts 


PSC 14" sq 


23.16 


stiff clay 


stiff clay 


1423 


3.899 



245 



Table C-1 (cont.) 



318 


TW488-3DR 


Massachusetts 


PSC 14" sq 


23.16 


stiff clay 


stiff clay 


1423 


1.524 


319 


NBTP2-EOD 


Massachusetts 


HP 12X74 


34.14 


si-sa-clay 


glacial till 


1806 


1.336 


320 


NBTP2-1DR 


Massachusetts 


HP 12X74 


34.14 


si-sa-clay 


glacial till 


1806 


1.128 


321 


NBTP2-6DR 


Massachusetts 


HP 12X74 


34.14 


si-sa-clay 


glacial till 


1806 


1.071 


322 


NBTP3-EOD 


Massachusetts 


HP12X74 


33.07 


si-sa-clay 


silty 


2126 


1.517 


323 


NBTP3-1DR 


Massachusetts 


HP12X74 


33.07 


si-sa-clay 


silty 


2126 


1.328 


324 


NBTP3-6DR 


Massachusetts 


HP12X74 


33.07 


si-sa-clay 


silty 


2126 


1.241 


325 


NBTP5-EOD 


Massachusetts 


CEP12.75" 


33.83 


si-sa-clay 


glacial till 


1632 


1.147 


326 


NBTP5-3DR 


Massachusetts 


CEP12.75" 


33.83 


si-sa-clay 


glacial till 


1632 


0.798 


327 


PRl-BORl 


Virginia 


PSC 24" sq 


31.88 


sand & silt 


silty sand 






328 


DD29-EOD 


Florida 


CEP 12.75" 


49.68 


clayey sand 


clayey 
sand 






329 


ND50-BOR1 


Ohio 


CEP 12" 


6.71 


silty clay 


si-clayey 
sand 


676 


0.849 


330 


NZ12-BOR1 


Mississippi 


HP 14X7 3 


11.89 


silt 


silt 


2224 


0.954 


331 


DWI-BORl 


S. Carolina 


PSC 24" sq 


27.46 


silty clay 


silty clay 


4742 


1.050 


332 


DW 1-BOR2 


S. Carolina 


PSC 24" sq 


27.52 


silty clay 


silty clay 


4742 


0.916 


333 


DW2-BORI 


S. Carolina 


HP14X73 


27.46 


si-sa-clay 


silty clay 


2753 


0.984 


334 


DW2-BOR2 


S. Carolina 


HP14X73 


27.52 


si-sa-clay 


silty clay 


2753 


0.910 


335 


DSl-BORI 


S. Carolina 


PSC 12" sq 


26.82 


cl-si-sand 


calcar sand 


1601 


1.319 


336 


DS1-BOR2 


S. Carolina 


PSC 12" sq 


26.85 


cl-si-sand 


calcar sand 


1601 


1.043 


337 


PX2-BOR1 


Arizona 


HP14X117 


14.02 


clay & sand 


cobble 






338 


PX3-EOD 


Arizona 


HP14X1 17 


15.24 


clay & sand 


cobble 






339 


PX3-BOR1 


Arizona 


HP14X117 


15.24 


clay & sand 


cobble 






340 


PX4-EOD 


Arizona 


CEP 14" 


6.83 


clay & sand 


clayey 
sand 


3207 


1.419 


341 


PX4-BOR1 


Arizona 


CEP 14" 


6.83 


clay & sand 


clayey 
sand 


3207 


1.145 


342 


PX5-BORI 


Arizona 


CEP 14" 


7.53 


clay & sand 


clayey 
sand 


2971 


1.081 


343 


PX6-BOR1 


Arizona 


PSC 16" sq 


7.01 


clay & sand 


clayey 
sand 


4235 


1.760 


344 


PX7-EOD 


Arizona 


PSC 16" sq 


6.1 


clay & sand 


clay 


4475 


1.902 


345 


PX7-BOR1 


Arizona 


PSC 16" sq 


6.1 


clay & sand 


clay 


4475 


1.623 


346 


CHI 1-42- 
BORl 


Wisconsin 


CEP 12.75" 


28.99 


sa-cl-silt 


silty clay 


1948 


0.829 


347 


SSTPD-BOR 


Sweden 


PSC 9.25" 
sq 


12.8 


silty sand 


silty sand 


285 


0.733 


348 


TSWID62/1- 
EOD 


Hong Kong 


PSC 19 69" 
cyl 


22.7 


sa-cl-silt 


sandy silt 


4359 


1.298 


349 


TSW/D62/1- 
BOR 


Hong Kong 


PSC 19.69" 
cyl 


22.7 


sa-cl-silt 


sandy silt 


4359 


0.917 


350 


TSW/HHK9/ 
1-EOD 


Hong Kong 


PSC 19.69" 
cyl 


23.6 


sa-cl-silt 


sandy silt 


4604 


1.208 


351 


TSW/HHK9/ 
1-BOR 


Hong Kong 


PSC 19.69" 
cyl 


23.6 


sa-cl-silt 


sandy silt 


4604 


0.949 


352 


TSW/D62/2- 
EOD 


Hong Kong 


HP12X120? 


29.7 


sa-cl-silt 


sandy silt 


4737 


0.976 



246 



Table C-1 (cont.) 



353 


TSW/D62/2- 
BOR 




HP 12X120'' 


29.7 


JLX ^X ljXXL 


canHv silt 


4737 


1.020 


354 


TSW/ 
IHK9/2-EOD 


Hong Kong 


HP 12X1 20? 


31.5 


ss-cl-silt 


sandy silt 


4804 


1.141 


355 


TSW/HHK9/ 
2-BOR 


Hong Kong 


HP12X120? 


31.5 


sa-cl-silt 


sandy silt 


4804 


1.104 


356 


ODIJ-EOD 


Oakland, CA 


OEP 24" 


8.47 


silty sand 


silty clayey 
sand 


7722 


2.209 


357 


OD2P-EOD 


Oakland, CA 


OEP 24" 


12.19 


silty sand 


silty sandy 
clay 


3047 


1.957 


358 


OD2P-BOR 


Oakland, CA 


OEP 24" 


12.19 


silty sand 


silty sandy 
clay 


3047 


1.370 


359 


OD2T-EOD 


Oakland, CA 


CEP 24" 


10.67 


silty sand 


silty sand 
& clay 


3616 


0.995 


360 


OD3H-EOD 


Oakland, CA 


OEP 42" 


30.63 


stiff clay 


clav w/ sa- 

^xtA y vv / k ? CI 

si-gr 


4639 


3.219 


361 


OD4L-EOD 


Oakland, CA 


CEP 24" 


19.51 


sandy clay 


silty sandy 
clay 


4399 


1.962 


362 


OD4P-EOD 


Oakland, CA 


CEP 24" 


17.07 


silty clay 


silty sandy 
clay 


3087 


2.543 


363 


OD4P-BOR 


Oakland, CA 


CEP 24" 


17.07 


silty clay 


silty sandy 
clay 


3087 


1.257 


364 


OD4T-EOD 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy 
clay 


3229 


2.412 


365 


OD4T-BOR 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy 
clay 


3229 


1.117 


366 


OD4W-EOD 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy 
clay 


3937 


2.229 


367 


OD4W- 
BOR2 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy 
clay 


3937 


1.534 


368 


OD4W- 
BOR3 


Oakland, CA 


CEP 24" 


18.38 


sandy clay 


silty sandy 
clay 


3937 


1.157 


369 


QC3-EOD 


New York 


PSC 54" cyl 


23.01 


sand 


dense sand 


6361 


3.530 


370 


QC3-14DR 


New York 


PSC 54" cyl 


23.01 


sand 


dense sand 


6361 


1.222 


371 


QC14-EOD 


New York 


PSC 14" cyl 


22.86 


sand 


dense sand 


1392 


1.122 


372 


QC 14-30DR 


New York 


PSC 14" cyl 


22.86 


sand 


dense sand 


1392 


1.163 


373 


NYSP-EOD 


New York 


HPl OX42 


33.5 


silty sand 


silty sand 
w/gr 


1388 


2.365 


374 


NYSP-BOR 


New York 


HP 10X42 


33.5 


silty sand 


silty sand 
w/gr 


1388 


1.399 


375 


TJFSSIA - 
BOR 


Florida 


PSC 24" sn 


15 


cl-si-sand 


silty clay 


3496 


0.644 


376 


UFSSIB - 
BOR 


Florida 


PSC 20" sq 


14.42 


cl-si-sand 


silty clay 


2611 


0.735 


377 


UFSS I O - 
BOR 


Florida 


PSC 24" sq 


8.5 


sa-si-clay 


silty clay 


5107 


0.820 


378 


UFSS13B - 
BOR 


Florida 


PSC 24" sq 


8.2 


sa-si-clay 


silty clay 


2771 


0.656 


379 


BIT20 - BOR 


Florida 


PSC 20" sq 


14.08 


silty sand 


sand 


2593 


1.230 


381 


HFLS3 - 
EOD 


Florida 


PSC 30" sq 


12.07 


sa-si-clay 


sandy clay 


7073 


1.222 


382 


HFLS4L - 


Florida 


PSC 30" sq 


22.4 


cl-si-limestone- 


limerock 


3354 


1.070 



247 





EOD 








sand 








383 


HFLS4L - 
BOR 


Florida 


PSC 30" sq 


22.4 


cl-si-limestone- 
sand 


limerock 


3354 


0.824 


384 


RBA30 - 
BOR 


Florida 


PSC 30" sq 


16.28 


silty sand 


silty sand 


4039 


1.094 


385 


RBB30W - 
BOR 


Florida 


PSC 30" sq 


13.35 


silty sand 


silty sand 


3461 


1.073 


386 


CC6 - BOR 


Florida 


PSC 18" sq 


16.18 


silty sand 


sand 


1388 


0.975 


387 


CC7 - BOR 


Florida 


PSC 14" sq 


23.23 


cl-si-sand 


silty sand 


1770 


0.978 


388 


CC14-BOR 


Florida 


PSC 14" sq 


21.18 


cl-si-sand 


silty sand 


1601 


0.847 


389 


49SB37 - 
EOD 


Florida 


PSC 30" sq 


7.13 


sandy clay 


silty 
limestone 


5058 


1.109 




N 


JO J 


Average 


1.426 


SD 


0.912 


GOV 


0.639 




3=2.33 


0.386 


P=3.0 


0.254 



Table C-2 Alabama CAPWAP (EQD+BOR) Data 



No 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 
(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


41 


FA 1 -EOD 


Alabama 


PSC 18"sq 


19.51 


silty sand 


silty sand 


1646 


912 


1.805 


42 


FAl-BORl 


Alabama 


PSC 18"sq 


19.66 


silty sand 


silty sand 


1646 


1143 


1.440 


43 


FAI-BOR2 


Alabama 


PSC 18"sq 


19.75 


silty sand 


silty sand 


1646 


1699 


0.969 


44 


FA2-EOD 


Alabama 


PSC 18"sq 


22.86 


silty sand 


silty sand 


2447 


1904 


1.285 


45 


FA2-BORI 


Alabama 


PSC 18"sq 


22.95 


silty sand 


silty sand 


2447 


2175 


1.125 


46 


FA2-BOR2 


Alabama 


PSC 18"sq 


23.01 


silty sand 


silty sand 


2447 


2664 


0.919 


47 


FA3-EOD 


Alabama 


PSC 24"sq 


19.51 


silty sand 


silty sand 


2780 


1512 


1.839 


48 


FA3-BORI 


Alabama 


PSC 24"sq 


19.54 


silty sand 


silty sand 


2780 


1366 


2.035 


49 


FA3-BOR2 


Alabama 


PSC 24"sq 


19.66 


silty sand 


silty sand 


2780 


2611 


1.065 


50 


FA4-EOD 


Alabama 


PSC 24"sq 


22.86 


silty sand 


silty sand 


3634 


1984 


1.832 


51 


FA4-BOR1 


Alabama 


PSC 24"sq 


22.89 


silty sand 


silty sand 


3634 


2687 


1.352 


52 


FA4-BOR2 


Alabama 


PSC 24"sq 


22.92 


silty sand 


silty sand 


3634 


3790 


0.959 


53 


FA5-EOD 


Alabama 


PSC 36"sq 


22.25 


silty sand 


silty sand 


5071 


2945 


1.722 


54 


FA5-BOR 


Alabama 


PSC 36"sq 


22.28 


silty sand 


silty sand 


5071 


4204 


1.206 




N 


14 


Average 


1.397 


SD 


0.383 


GOV 


0.274 




3=2.33 


0.828 


3=3.0 


0.656 



248 





nil o 

rable C-3 Oa 


kland, CA CAPWAP (EOD+BOR) Data 


No 


Pile-Case 
Number 


Location 


Pile 

Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 


CAPWAP 

Itr W Ar 


Rdavisson 
Rcapwap 


Side 


Tip 




OFM T TTOF* 
yJL) Ij-nAJL) 


V^alvlallU, V 


OFP 7/1" 


R AT! 


silty sand 


silty clayey sand 


7777 
/ / zz 




7 7nq 


jD I 






OFP 74." 


1 9 1 Q 


silty sand 


silty sandy clay 


^047 


1 SS7 


1 QS7 




VJUZ r - r> K 


OnWnnrl CA 


OFP 7/1" 


1 9 1 Q 


silty sand 


silty sandy clay 


^047 


7774 

ZZZH- 


1 ^70 




\JL)Z 1 -liUiJ 


OnHnnH CA 


CW> 7zl" 


lU.O / 


silty sand 


silty sand & clay 






\j.yyD 






V^oJvlallLl, V. /A 


OFP /L7" 




stiff clay 


clay w/ sa-si-gr 




1441 


^ 71Q 




V-' i-'H-l-/ - JJ/V-' i-' 


vyoJvlallLl, v./A 


PFP 74." 


1Q SI 


sandy clay 


silty sandy clay 


4^QQ 


7747 

ZZt-Z 






yJLJ'^r-LjyjLJ 


OnHanH CA 


r"FP 74" 
v^L/r Zt- 


1 7 07 


silty clay 


silty sandy clay 




1714 

1 Z IH 


7 S4^ 

Z. 




OF»/l D ROD 


Oakland, CA 


CEP 24" 


17.07 


silty clay 


silty sandy clay 


3087 


Z^J J 


1 9S7 
1 .ZJ / 


364 


OD4T-EOD 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy clay 


3229 


1 ^^Q 


7 417 

Z.T- 1 z 


365 


OD4T-BOR 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy clay 


3229 


78Q 1 

ZO" 1 


1117 
1.11/ 


366 


OD4W-EOD 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy clay 


3937 


1 7f>fi 


9 77Q 
z.zz^ 


367 


OD4W-BOR2 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy clay 


3937 


2567 


1 S^4 


368 


OD4W-BOR3 


Oakland, CA 


CEP 24" 


18.38 


sandy clay 


silty sandy clay 


3937 


3403 


1.157 




N 


13 


Average 


1.843 


SD 


0.671 


GOV 


0.364 




P=2.33 


0.908 


|3=3.0 


0.688 



Table C-4 South Caro 



ina CAPWAP (EOD+BOR) Data 



No 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


268 


BC79-EOD 


S.Carolina 


PSC 24" oct 


23.47 


si-cl-sand 


calcar sand 


2277 






269 


BC79-BORL 


S.Carolina 


PSC 24" oct 


23.5 


si-cl-sand 


calcar sand 


2277 


2447 


0.931 


270 


BC64-EOD 


S.Carolina 


PSC 24" oct 


18.59 


si-cl-sand 


calcar sand 


5071 






271 


BC64-BORL 


S.Carolina 


PSC 24" oct 


18.62 


si-cl-sand 


calcar sand 


5071 


5004 


1.013 


278 


MBl-EOD 


S. Carolina 


PSC 16"sq 


18.9 


sand 


silty sand 


3590 


756 


4.749 


279 


MBl-BOR 


S. Carolina 


PSC 16"sq 


19.2 


sand 


silty sand 


3590 


2326 


1.543 


280 


MB2-BOR 


S. Carolina 


HP14x89 


20.12 


silty sand 


calcar. silt 


3990 


2362 


1.689 


281 


MB3-BOR 


S. Carolina 


OEP 16" 


20.12 


silty sand 


calcar. silt 


4146 


2540 


1.632 


282 


Sl-EOD 


S. Carolina 


OEP 24" 


24.84 


clayey sand 


sandy silt 


2651 


2046 


1.296 


283 


Sl-BOR 


S. Carolina 


OEP 24" 


24.84 


clayey sand 


sandy silt 


2651 


2687 


0.987 


284 


S2-EOD 


S. Carolina 


HP14x73 


23.77 


clayey sand 


sandy silt 


1415 


956 


1.480 


285 


S2-BOR 


S. Carolina 


HP14x73 


23.77 


clayey sand 


sandy silt 


1415 


1366 


1.036 


331 


DWl-BORl 


S. Carolina 


PSC 24" sq 


27.46 


silty clay 


silty clay 


4742 


4515 


1.050 


332 


DW 1-BOR2 


S. Carolina 


PSC 24" sq 


27.52 


silty clay 


silty clay 


4742 


5178 


0.916 


333 


DW2-BORI 


S. Carolina 


HP14X73 


27.46 


si-sa-clay 


silty clay 


2753 


2798 


0.984 


334 


DW2-BOR2 


S. Carolina 


HP14X73 


27.52 


si-sa-clay 


silty clay 


2753 


3025 


0.910 



249 



Table C-4 (cont.) 



335 


DSl-BORI 


S. Carolina 


PSC 12" sq 


26.82 


cl-si-sand 


calcar sand 


1601 


1214 


1 ^1 Q 


336 


DS1-BOR2 


S. Carolina 


PSC 12" sq 


26.85 


cl-si-sand 


calcar sand 


1601 


1535 


1 043 




N 


16 


Average 


1.411 


SD 


0.930 


( 


:ov 


0.659 




|3=2.33 


0.306 


p=3.0 


0.199 



Table C-5 Florida CAPWAP (EOD+BOR) Data 





Pile-Case 
Number 


Location 


Pile 
Type 


Depth 
(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 

TFPW A P 

(kN) 


Rdavisson 
Rcapwap 


Side 


Tin 
lip 


78 


WC3-EOD 


Florida 


PSC24"sq 


8.32 


Is -d sand 


dense 


2713 


2264 


1.198 


79 


WC3-BORI 


Florida 


PSC24"sq 


8.38 


Is -d sand 


dense 


2713 


2251 


1.205 


80 


WC3-BOR2 


Florida 


PSC24"sq 


8.38 






2713 


2384 


1.138 


81 


WC6-EOD 


Florida 


PSC24"sq 


8.63 


Tc -Hsand 


dense 


2015 


2002 


1.006 


82 


WC6-BOR1 


Florida 


PSC24"sq 


8.69 


Is -d sand 


dense 


2015 


2135 


0.944 


83 


WC6-BOR2 


Florida 


PSC24"sq 


8.38 


Is -d sand 


dense 


2015 


1971 


1.022 


84 


WB9-BOR 


Florida 


PSC30"sq 


39.17 




clayey 


4003 


4186 


0.956 


85 


WB15-BOR 


Florida 


PSC30"sq 


31.58 


sand 


silf-clav 

k311L ^iLiy 


3648 


3581 


1.019 


105 


STl-EOD 


Florida 


PSC 18"sq 


13.41 




rarl> sand 

^ lU 1/ k3UllVl 


1530 


2246 


0.681 


106 


ST2-EOD 


Florida 


PSC 18"sq 


12.19 




rarl> sand 


2269 


2740 


0.828 


140 


A3-EOD2 


Florida 


VC 24"sq 


27.52 




sand 


4261 


1637 


2.603 


141 


A3-BOR2 


Florida 


VC 24"sq 


27.55 


rlavpv sand 


sand 


4261 


2055 


2.073 


142 


A3-BOR3 


Florida 


VC 24"sq 


27.61 


rlavpv sand 


rlavev sand 

^iciy \j y k3uiivi 


4261 


4115 


1.035 


143 


A14-DD1 


Florida 


VC 24"sq 


13.72 


sandv olav 


sand 


NA 


3043 




144 


A14-DD2 


Florida 


VC 24"sq 


14.33 


sandv olav 


sand 


NA 


3296 




145 


A14-BOR1 


Florida 


VC 24"sq 


17.83 


clayey sand 


sand 


NA 


2687 




146 


A14-BOR2 


Florida 


VC 24"sq 


17.92 


clayey sand 


sand 


NA 


4279 




147 


A25-EOD 


Florida 


VC 24"sq 


16.79 


clayey sand 


sand 


3180 


2042 


1.557 


148 


A25-BOR1 


Florida 


VC 24"sq 


16.82 


clayey sand 


sand 


3180 


2469 


1.288 


149 


A25-BOR2 


Florida 


VC 24"sq 


16.89 


clayey sand 


sand 


3180 


2011 


1.581 


150 


A25-BOR3 


Florida 


VC 24"sq 


16.92 


clayey sand 


sand 


3180 


1966 


1.617 


151 


AI6-EOD 


Florida 


PSC18"sq 


18.47 


sandy clay 


sand 


1401 


996 


1.407 


152 


A16-BOR1 


Florida 


PSC18"sq 


18.47 


sandy clay 


sand 


1401 


1254 


1.117 


153 


A16-BOR2 


Florida 


PSC18"sq 


18.59 


sandy clay 


sand 


1401 


1317 


1.064 


154 


A41-EOD 


Florida 


VC 24"sq 


15.85 


clay 


sand 


2331 


1917 


1.216 


155 


A41-BOR1 


Florida 


VC 24"sq 


15.85 


clay 


sand 


2331 


2237 


1.042 


156 


A41-BOR2 


Florida 


VC 24"sq 


16.09 


clay 


sand 


2331 


2513 


0.928 


157 


AlOl-EOD 


Florida 


VC 24"sq 


18.84 


clay 


clayey sand 


3612 


2300 


1.570 


158 


AlOl-BORI 


Florida 


VC 24"sq 


18.84 


clay 


clayey sand 


3612 


2976 


1.214 


159 


A101-BOR2 


Florida 


VC 24"sq 


18.93 


clay 


clayey sand 


3612 


3572 


1.011 


160 


A133-EOD 


Florida 


VC 24"sq 


31.67 


clayey sand 


sandy clay 


3594 


1383 


2.599 


161 


A133-BOR 


Florida 


VC 24"sq 


31.97 


clayey sand 


sandy clay 


3594 


3470 


1.036 


162 


A145-EOD 


Florida 


VC 24"sq 


31.36 


clayey sand 


sand 


4341 


1570 


2.765 



250 



Table C-5 (cont.) 



1 A'J 
iOJ 


A 1 /I ^ ROD 1 


Florida 


Z4 sq 


'i 1 'iA 


clayey sand 


sand 


A^AA 


98^ 1 
ZoJ 1 


1 ^97 
1 .J2.J 


1 A/1 


A 1 /I ^ nopo 
A14j-r>UKZ 


Florida 


Z4 sq 


'J 1 

J l.jy 


clayey sand 


sand 


A^AA 


778^ 


1 989 
1 .ZoZ 


1 f.'^ 
10 J 


v^oo-Ijvjk 


Florida 


pC/~^0/1 "cn 


Z / 


clayey sand 


sand 


999A 
ZZZ4 


9^0Q 
ZjUV 


88A 
U.ooO 


100 




Florida 


PQ/^O/l "cin 

roV^Z4 sq 


07 7 1 
Zj. / 1 


clayey sand 


sand 


999/1 
ZZZ^ 


9977 
ZZj J 


O QQA 
U.VVO 


10 / 


r^R^ ROP 


Florida 


vi^ sq 


1 A 1 G 
10. lo 


clayey sand 


sand 


^^AM 
JJOU 


9^97 

ZjZ / 


9 900 


luo 






V j\j sq 


1 f\ Af\ 




c:\Y\c\'\j /^Idi? 
oaliuy Olay 




9SQS 

Z-J"0 


9 MO 




CRT 1 -RORT 


Florida 


Vr ^0"sn 


26.12 




\^\.ix\ c y ddiiLi 






1 76^ 




PRI l-FORT 


Fl r\t"\ H n 


V ?>L| 


7f> 1 S 

Z,\J. i J 


i-itiycy L^diiLi 


i-itiycy L^ciiiLi 




9S49 


9 946 


171 


rRi7-RnRi 


Florida 


vr ^0"sn 


Z, J.\JO 


i.i£i y c y ddtiiLi 


i.i£i y c y dtiiiu. 


673Q 
\j 1 oy 


3648 


1.847 


172 




Florida 




23.71 


i.i£i y c y duiiLi 


i.i£i y c y dciiiLi 


6739 

\j 1 oy 


333? 


? 0?3 


173 


rR17-RnRT 


Florida 




23.74 


L/iciy c y duiiLi 


i.i£i y c y duiiLi 


6739 

V/ / oy 


3038 

JO 


2.218 


1 / H- 


PRl 7 nPT 


rioriud 


VP ^n"Gn 

V j\j sq 


ZJ.O'H- 


Clayey sdiiu 


Clayey saiiu 


O / oy 


77SQ 

J / JV 


1 7Q7 
1 . / yj 


1 / J 


/"^ROO ROP 


Florida 


vr ^n"cn 

j\j sq 


ZH-.H-o 


clayey sand 


sand 


98An 
ZoOU 


97^7 

Z / J J 


1 07Q 
1 Ajjy 


1 7A 
1 /O 


f^ROO ROPF 


Florida 


v^^ju sq 


ZJ.ZI 


clayey sand 


sand 


98An 
ZoOU 


1 Q7^ 
1 V /3 


1 448 
1 .44o 


1 77 
1 / / 


/^R9Q ROPT 


Florida 


vr ^n"cn 
vi^ sq 


9^ 7 A 
Zj. /O 


clayey sand 


clayey sand 


■H-U / V 


j43Z 


1 1 89 
1 . 1 oZ 


1 7C 

I/O 


l^oZV-liVjKL 


Florida 


vi^ sq 


9^ 7 A 
Zj. /O 


clayey sand 


clayey sand 


/1M7Q 
4U / V 


1 QQ7 
1 VV / 


9 0/17 


1 7Q 

1 /y 


/"^Ro^ ROP 1 


Florida 


vr '^n"cn 
V jv sq 


9'^ Q'^ 


clayey sand 


clayey sand 


A^n8 
OjUo 


7A 1 9 
OOlZ 


1 809 
1 .oUZ 


loU 


/"^Ro^ ROP9 


Florida 


vr '^n"cn 
V jv sq 


lA 


clayey sand 


clayey sand 


A^n8 
03Uo 


A99 1 
4ZZ i 


1 ^49 
1 . J4Z 


loi 


/"^Ro^ ROPT 


Florida 


vr '^n"cn 
V jv sq 


9A 1 1 
Z4. 1 1 


clayey sand 


clayey sand 


A^n8 
OjUo 


AO A 7 
4U4j 


1 Al 
1 .OIU 


loZ 


r^R/1 1 T70P 

l^r>41-liUK 


Florida 


jV sq 


1 Q 79 

ly. / Z 


sandy clay 


sandy clay 


A979 
OZ / Z 


7819 
JolZ 


1 A/1^ 
1 .04j 


lOJ 


r'RzLl ROP 


Florida 


vr ^n"cn 
V jKj sq 


1 Q 79 

1^7. /Z 


sandy clay 


sandy clay 


A979 
OZ / Z 


778 1 


1 A^Q 
1 .03V 


1 


r'RzLl ROPT 


Florida 


vr ^n"cn 
vi^ sq 


1 Q Q7 
Vy.yj 


sandy clay 


sandy clay 


A979 
OZ / Z 


9 1 ^7 

Zl J / 


9 Q08 
Z.VUo 


lo3 


r> Z - 


Florida 


ro^^z^ sq 


1 Q 


clayey sand 


sand 


A97n 
4Z l\j 


9171 
Zl / i 


1 QA7 
1 .VO / 


1 CA 
loO 


r^ROA ROP 


Florida 


roL-Z4 sq 


1 Q nc 

IV. Uo 


clayey sand 


sand 


/i97n 

4Z /U 


97^7 


1 ^^1 

1 .J J 1 


1 R7 
lo / 


/~^R9A FOP 


Florida 


roV^Z4 sq 


1 Q 7^ 

Vy. ID 


clayey sand 


sandy clay 


A97n 
4Z /U 


7 1 8^ 


1 741 
1 . j41 


1 88 
loo 


r'ROA ROP9 


Florida 


j^oV^Z4 sq 


1 Q 8 1 
IV. oi 


sandy clay 


sandy clay 


A97n 
4Z l\j 


9^0A 
ZjU4 


1 70^ 
1 . I\JJ 




P09 ROP 1 


Florida 


P<vr 1 8"cn 

ro^w^lo sq 


^ 7'^ 
J. 1 J 


sand 


dense sand 


1 9 1 Q 

IZl V 


1 7^9 


Q09 
U.VUZ 


ZjO 


rvJZ-DvJKZ 


Florida 


roV^lo sq 


A M7 
O.U / 


sand 


dense sand 


1 9 1 Q 
IZl V 


1 1 7/1 
11/4 


1 078 


Ld I 


P09 ROPT 


Florida 


ro^^lo sq 


A 98 
O.Zo 


sand 


dense sand 


1 9 1 Q 
iZ i V 


1 9^0 
IZjU 


Q7^ 
U.V / J 


Loo 


PO 1 Q ROP 


Florida 


ro^io sq 


zL A'^ 


sand 


dense sand 


1 097 
lUZj 


1 774 
1 J J4 


7A7 

u. /o / 


ZjV 


PO 1 Q FOn 


Florida 


ro^lo sq 


^ 94 


sand 


dense sand 


1 n97 

lUZj 


1 OQO 
lUVU 


Q7Q 




PO 1 Q POP T 


Florida 


ro*^lo sq 


^ 'iA 
J. jO 


sand 


dense sand 


1 n97 

lUZj 


1 C\A ^ 
1U4J 


O Q7Q 
U.V / V 


9A1 
Z4i 


FP^ ROPl 


Florida 


roV^Z4 sq 


9^ Q7 


sand 


sand 




9Q97 
ZVZ / 


1 9QQ 
1 .ZVV 


Z4Z 


FP^ ROP9 


Florida 


r oV^Z4 sq 


9A n'^ 


sand 


sand 


7807 


A^ 97 
41Z0 


Q99 
U.VZZ 




FP^ ROPT 


Florida 


roK^z.^ sq 


9A 1 ^ 
ZO. i J 


sand 


sand 


7807 


9A 1 1 
ZO 1 1 


1 4^7 
1 .43 / 


Z44 


17P77 ROP 
liK / / -dUK 


Florida 


roV^Z4 sq 


1 C ^A 
lo. jO 


clayey sand 


cl-si-sand 




77A7 


9 9 1 O 
Z.ZIU 


Z-H-j 


FP77 ROPT 


Florida 


ro^^z^ sq 


1 8 A8 
io.Oo 


clayey sand 


cl-si-sand 


7zL77 


AA9.A 
44 o4 


1 A^8 
1 .03o 


Z^O 


RRl 1. For> 


Florida 


vr ^n"cn 


98 9Q 
Zo.ZV 


clayey sand 


sand 


AAl^ 


7114 
J 1 14 


1 477 
1 .43 / 


Z^ / 


RR 1 1. ROP 1 Q 


Florida 


vr ^n"cn 


98 '^9 
Zo. jZ 


clayey sand 


sand 


AAl^ 


4UVZ 


1 0Q4 
1 .WV4 


Z4o 


RR 1 ROPTh 


Florida 


vr '^n"cn 
V jv sq 


98 '^9 
Zo.^Z 


clayey sand 


sand 


AAl^ 
44 / J 


7Q^Q 
jV3V 


1 1 70 
1 . 13U 


249 


BB 13-BOR2a 


Florida 


VC 30"sq 


28.71 


clayey sand 


sand 


4475 


4760 


0.940 


250 


BB13-BOR2b 


Florida 


VC 30"sq 


28.71 


clayey sand 


sand 


4475 


4671 


0.958 


251 


BB I3-BORL 


Florida 


VC 30"sq 


28.8 


clayey sand 


sand 


4475 


4008 


1.117 


252 


BB19-BORa 


Florida 


VC 30"sq 


27.13 


sand 


sand 


5169 


4155 


1.244 


253 


BB19-BORb 


Florida 


VC 30"sq 


27.13 


sand 


sand 


5169 


4666 


1.108 


254 


BB19-BORL 


Florida 


VC 30"sq 


27.19 


sand 


sand 


5169 


6512 


0.794 



251 



Table C-5 (cont.) 





SdSdA^-lIAJL) 


Florida 


vi^ sq 


OA AA 


sand 


clay 




J lOJ 


n 8^7 
U.oj / 


zjO 




Florida 


vi^ sq 


9/1 /t C 


sand 


clay 




7^ 1 1 

/J 1 / 


n A^Q 


Z3 / 


RR9A ROPTK 


Florida 


vi^ sq 


9zl 


sand 


clay 


4yj3 


7^71 


A^A 


Zjo 


RR9/1 ROP9o 


Florida 


vi^ sq 


9/1 


sand 


clay 


/IQ^^ 


c/i9n 
o4zU 


n ^88 

U.joo 




T'^1'^9/1 ROP9K 
Ij 1 jz4-dUKzD 


Florida 


vi^ sq 


9/1 A'^ 


sand 


clay 


/IQ^^ 


7C7'^ 
lolD 


n A9Q 


9 AH 
ZOU 


RR9zl ROPT 


Florida 


V sq 


94 AQ 


sand 


clay 




A9zLl 
OZ-H-l 


IQA 


ZU i 


RR9Q ROR 


r \\Jii\Xa. 


V j\j sq 


9^ QO 


sand 


sand 


jyjjj 




Q9fi 


9f>9 


RR9Q-RnRT 


H 1 r\T"i H n 


V J\\ 


9^ Qf> 


sand 


sand 






Q88 




ARF6-RnR 


T^l on H n 




17.54 


ail K^LcLj C y dclllLl 


i.i£i y c y dciiiu. 




1611 


1 995 


264 


ARF6-RnRT 


T^l on H n 


PSr 24" sn 


17.84 


SI/ L/i£i y c y dciiiLi 


i.i£i y c y dciiiLi 


3345 


3474 


963 


76^ 


ARnn-RORT 


T^l on H n 


PSr 24" sn 


14 08 


i-i£iy c y dciiiLi 


llTTlPQtonP 


4742 




983 

VJ. 70 J 




ARH9-ROR 


H Ion H !1 


PSr 94" 


10 Q 


cilt/cilf\/ r'liix/ 
siii/siiLV i^itiy 


1 ITTll^Cf oni^ 
lliilCSLUIIC 


9S1 8 

Z, J 1 o 




701 


7^i7 

z,u / 


ARH9 RORT 


T-H 1 1^1*1 Q 


P^nP 94" QH 

r ov^ ZH- sq 




Sllt/SllLy K^iay 


li m c frw\ 
lllllCSHJllC 


9S1 8 

ZJ 1 o 


4009 


f>l S 

w.ui J 


ZoO 


ivi-/ ZZ - ij/Vj J-/ 


Florida 


roi^ i-H- sq 




clay 


sand 




1 1 '^zl 
1 i 


"^09 
J. jUZ 


287 


DD22-BOR 


Florida 


PSC 14 sq 


27.74 


clay 


sand 


3745 


2309 


1.622 


288 


DD23-EOD 


Florida 


CBP 12.75 


24.99 


clay 


sand 


2206 


681 


3.239 


289 


DD23-BOR 


Florida 


CBP 12.75 


25.09 


clay 


sand 


2206 


1232 


1.791 


328 


DD29-EOD 


Florida 


CBP 12.75" 


49.68 


clayey sand 


clayey sand 


NA 


1561 




375 


UFSSIA - BOR 


Florida 


PSC 24" sq 


15 


cl-si-sand 


silty clay 


3496 


5427 


0.644 


376 


UFSSIB - BOR 


Florida 


PSC 20" sq 


14.42 


cl-si-sand 


silty clay 


2611 


3554 


0.735 




UFSS I O - 




















377 


BOR 


Florida 


PSC 24" sq 


8.5 


sa-si-clay 


silty clay 


5107 


6228 


0.820 




UFSS13B - 




















378 


BOR 


Florida 


PSC 24" sq 


8.2 


sa-si-clay 


silty clay 


2771 


4226 


0.656 


379 


BIT20 - BOR 


Florida 


PSC 20" sq 


14.08 


Silty sand 


sand 


2593 


2108 


1.230 


380 


BIT21 - BOR 


Florida 


PSC 20" sq 


11.09 


cl-si-sand 


silty sand 


1637 


1606 


1.019 


381 


HFLS3 - BOD 


Florida 


PSC 30" sq 


12.07 


sa-si-clay 


sandy clay 


7073 


5787 


1.222 












cl-si-limestone- 












382 


HFLS4L - BOD 


Florida 


PSC 30" sq 


22.4 


sand 


limerock 


3354 


3136 


1.070 












cl-si-limestone- 












383 


HFLS4L - BOR 


Florida 


PSC 30" sq 


22.4 


sand 


limerock 


3354 


4070 


0.824 


384 


RBA30 - BOR 


Florida 


PSC 30" sq 


16.28 


Silty sand 


silty sand 


4039 


3692 


1.094 




RBB30W - 






















I > V / K 


Florida 


per" '?0" cn 




oilty sand 


silty sand 




3225 


1 07'? 


JOO 




Florida 


ro<^ lo sq 


iO. io 


Silty sand 


sand 


1788 

1 JOO 


1423 


M Q7^ 


JO I 


V^V^ / - Dv-'K 


Florida 


ro^ 1^ sq 


9'? 9'? 


cl-si-sand 


silty sand 


1 770 


1810 


078 

u.y / o 


JOO 


CC^A COR 


Florida 


per" l/L" cn 

rol^ sq 


91 18 
Z i . 1 o 


cl-si-sand 


silty sand 


1 A01 


1890 


8zL7 


389 


49SR37 - FOD 


PI on H n 


PSC 30" sn 


7 13 


odiiLiy i^iciy 


QlltV llTTlPQtonP 


5058 


4559 


1 109 


















N 


107 


















Average 


1.324 


















SD 


0.571 


















GOV 


0.431 




















3=2.33 


0.564 


















p=3.0 


0.412 



252 



Table C-6 Louisiana CAPWAP (EOD+BOR) Data 



No 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 


CAPWAP 
IbrWAr 


Rdavisson 
Rcapwap 


olue 


Tir» 

lip 




FT ^-FDD 


Lll i 1 £ll I cl 




9S 69 


ftiiiy cidy 


ftllLy ftallU 


177Q 

L 1 1 y 


6ns 


9 940 




FT 3-RnT{ 


L W U 1 ft 1 £ll I £l 


IT v} V- ftU 


25 69 


ftiiiy cidy 


ftllLy ftallU 


177Q 

1. 1 1 y 


1210 


1.470 


67 


FT 3-F}nR? 


T otiiQinnn 

L VJ U-l ft 1 £ll I £l 


IT OV--Z,T^ ftU 


25 69 


ftiity ciciy 


ftllLy ftdiiu 


1779 

1 / / y 


1 557 


1.143 


791 


T R3-Fnr) 


T^pnnpr T A 

IxCIIIICl , L^y\ 


PSr 24" sn 


24.84 


cldy 


Sand 


1842 


969 

Z.U7 


6 848 






Tc (^tiTif^T" T A 

JVCIIIICl, L^r\ 


X OV^ Z,T- ftU 


74 99 


cldy 


Sand 


1 849 


Q1 7 


7 070 

z,. wz,w 




T R3-RnR? 


T^pnnpv T A 


PSr ?4" sn 

IT OV^ Z/T^ ftU 


?4 99 


cldy 


Sand 


1842 




1.201 


?94 


T R3-RnR3 


T^pnnpv T A 


PSr ?4" sn 

IT OV^ Z/T- ftL[ 


?4 99 


cldy 


Sand 


1842 


1677 


1 098 


?9S 


T R4-Fnr) 


T^pnnpv T A 


PSr 30" sn 

V OV^ JV/ ftL[ 


?4 99 


cldy 


Sand 


2273 


202 


1 1.252 


z.y\j 


T R/l-ROR 1 


rC f*tlTl^*r T A 
JVCIIIICl, L^/\ 


X Ov^ 0\J ftL[ 


9S 91 

Z, J .Z, 1 


cldy 


Sand 


997^ 


887 


9 S6^ 


791 

jLy 1 


T R4-RnR? 


T^pnnpr T A 

XxCIIIICl , L^y\ 


PSr ^0" sn 


25.27 


cldy 


Sand 


2273 


1999 


1 750 


298 


LR4-ROR3 


fCpnnpr T A 


PSr 30" so 


25.3 


cldy 


Sand 


2273 


1521 


1.494 


299 


LB4-BOR4 


Kenner, LA 


PSC 30" sq 


25.3 


clay 


Sand 


2273 


1603 


1.418 


300 


LB5-EOD 


Kenner, LA 


PSC 30" sq 


24.99 


clay 


Sand 


NA 


263 




301 


LB5-BOR1 


Kenner, LA 


PSC 30" sq 


24.99 


clay 


Sand 


NA 


952 




302 


LB5-BOR2 


Kenner, LA 


PSC 30" sq 


24.99 


clay 


Sand 


NA 


1402 




303 


LB5-BOR3 


Kenner, LA 


PSC 30" sq 


25.3 


clay 


Sand 


NA 


1591 




304 


LB5-BOR4 


Kenner, LA 


PSC 30" sq 


25.3 


clay 


Sand 


NA 


1752 




305 


LB6-EOD 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2411 


404 


5.968 


306 


LB6-BOR I 


Kenner T A 

IVwl II Iwl , 1 , 1 \ 


PSC 36" cvl 


24.69 


clay 


Sand 


2411 


883 


2.730 


j\j I 




rv n n (^r T A 
JVCIIIICl, \-ir\ 




74 69 


clay 


OdllU 


941 1 


1 ^99 


1 894 


308 


T R6-ROR3 


TCpnnpr T A 

XX\^llll\^X, 1 . I \ 


PSC 36" cvl 


24.99 


clay 


Sand 


2411 


1767 


1.364 


309 


LB6-BOR4 


Kenner, LA 


PSC 36" cyl 


24.99 


clay 


Sand 


2411 


2300 


1.048 


310 


LB7-EOD 


Kenner, LA 


PSC 36" cyl 


24.6 


clay 


Sand 


2402 


457 


5.256 


311 


LB7-BOR1 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


875 


2.745 


312 


LB7-BOR2 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


1279 


1.878 


313 


LB7-BOR3 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


1891 


1.270 


314 


LB7-BOR4 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


2260 


1.063 



N 

Average 
SD 
GOV 

I p=3.0 



Table C-7 Massachusetts CAPWAP (EOD+BOR) Data 



No 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


115 


GZZ5-EOD 


Boston MA 


CEP 14" 


26.52 


till-clay 


till 


2064 


952 


2.168 


116 


GZ05-E0D 


Boston MA 


CEP 14" 


16.46 


till-clay 


till 


2135 


912 


2.341 


117 


GZCC5-EOD 


Boston MA 


CEP 14" 


24.38 


till-clay 


till 


2002 


2189 


0.915 


118 


GZL2-EOD 


Boston MA 


CEP 14" 


25.3 


till-clay 


till 


2847 


1188 


2.396 


119 


GZP14-EOD 


Boston MA 


CEP 14" 


18.44 


till-clay 


till 


1735 


1357 


1.279 



253 



Table C-7 (cont.) 



1 ir\ 

iZU 




DOS ton iviA 




1 1 11 


till -clay 


fill 
nil 


1 1 1 
1 1 iz 


iUuj 


1 M/tA 


1 91 






PFP M" 




frill /^lQ\r 
Llll-Clay 


fill 


777/1 

ZZZt- 








DT991-FOD 


iViCl ft fttH^IILlSCLL J 


PSr 14" sn 

IT OV-- iT^ ftU 


1Q 7 

1 7.Z 


G?i-Gi 

ftd ftidd y 


Tinp GnnH Ri Gilt 

llllC ftdllLl C3C ftlll 


1477 










A/Tn c G n r* n 1 1 G f G 

i VI tl O ?) tH^ 1 1 U ?) C L L ?) 


PSr 14." 


IQ 7 


Gil -Gi -r*! n\7 
ftd ftlddV 


Ti Tif* G n Tirl Hi gi If 
IIIIC ftdllU ex. ftllL 


1477 

It- / / 




1 1 87 




1 VV '-rOO i—iyjl-J 


A/Tn GG!i r'riii Gf'tf g 


PSr 14." sn 


7^ \f\ 

ZJ . lU 


Gfl TT CX n\7 

ftLiii cidy 


Gtl TT r'l n \i 
ft nil cidy 


147^ 






J 1 o 


J. VV T^OO -UV^lV 


IVTn G G ?i (^h 1 1 G pttG 


PSr 14" sn 

IT OV^ 1 1 ftl^ 


7^ 16 


Gtl TT p1 n\7 


Gtl TT r*lnv 
ft Llll cidy 


1423 


934 


1.524 


J 1 " 


NRTP?-Fnr) 


IVTn GGHphll GPttG 
iVAtlftfttldlLlftCLLft 


HP1 ?X74 


34.14 


G1 -GH-pI 

fti ft ti i.iti y 


O'lnr'i^il fill 

^Idddl Llll 


1 806 


1 35? 

U JZ 


1 336 




NTRTP? ROR 
IM Jj i I Z- Ov7l\ 


iViaftftaCIlUftcLLft 


HP! 9V7A 


^4. 14 


ftl-fta-Cldy 


gldCldl llll 


loWD 


IDUl 


1 1 78 

1 . IZo 


321 


NBTP2-BOR 


Massachusetts 


HP12X74 


34.14 


si-sa-clay 


glacial till 


1806 


IDoD 


1 071 
1 .U / 1 


322 


NBTP3-EOD 


Massachusetts 


HP12X74 


33.07 


si-sa-clay 


silty 


2126 


1 zLH 1 


1 ^17 
1 .J 1 / 


323 


NBTP3-BOR 


Massachusetts 


HP12X74 


33.07 


si-sa-clay 


silty 


2126 


1 Am 

IDUl 


1. jZo 


324 


NBTP3-BOR 


Massachusetts 


HP12X74 


33.07 


si-sa-clay 


silty 


2126 


1 / 1 J 


A 1AA 
1.Z41 


325 


NBTP5-EOD 


Massachusetts 


CEP12.75" 


33.83 


si-sa-clay 


glacial till 


1632 


1423 


1 1 zL7 
1 . 14 / 


326 


NBTP5-BOR 


Massachusetts 


CEP12.75" 


33.83 


si-sa-clay 


glacial till 


1632 


2046 


7Q8 




N 


17 


Average 


1.515 


SD 


0.758 


COV 


0.500 




p=2.33 


0.555 


p=3.0 


0.392 



Table C-8 Nebraska CA] 


PWAP (EOD+BOR) Data 


No 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


1 


FNl-EOD 


Omaha NE 


HP10x42 


21.95 


silty clay 




1352 


1023 


1.322 


2 


FNI-BORl 


Omaha NE 


HPIOx42 


21.98 


silty clay 




1352 


1668 


0.811 


3 


FN1-BOR2 


Omaha NE 


HPIOx42 


22.25 


silty clay 




1352 


1917 


0.705 


4 


FN2-EOD 


Omaha NE 


PSC12"sq 


19.81 


silty clay 




1592 


1005 


1.584 


5 


FN2-BOR 


Omaha NE 


PSC12"sq 


19.81 


silty clay 




1592 


1357 


1.173 


6 


FN3-EOD 


Omaha NE 


PSC14"sq 


17.07 


silty clay 




1681 


796 


2.112 


7 


FN3-BOR 


Omaha NE 


PSC14"sq 


17.07 


silty clay 




1681 


1321 


1.273 


8 


FN4-EOD 


Omaha NE 


CEP12.75" 


20.12 


silty clay 




1263 


1085 


1.164 


9 


FN4-BOR 


Omaha NE 


CEP12.75" 


20.12 


silty clay 




1263 


1281 


0.986 




N 


9 


Average 


1.237 


SD 


0.423 


COV 


0.342 




p=2.33 


0.638 


3=3.0 


0.489 



254 



Table C-9 Oklahoma CAPWAP (EOD+BOR) Data 



No 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 


CAPWAP 
IbrWAr 


Rdavisson 
Rcapwap 


Side 


Tip 


14 


FOl-EOD 


Oklahoma 


CEP 26" 


18.35 


silty sand 


silty sand 


2660 


2206 


1.206 


15 


FOl-BOR 


Oklahoma 


CEP 26" 


18.35 


silty sand 


silty sand 


2660 


3114 


0.854 


16 


F02-E0D 


Oklahoma 


PSC24"oct 


19.2 


silty sand 


silty sand 


3381 


2358 


1.434 


17 


F02-B0R 


Oklahoma 


PSC24"oct 


19.23 


silty sand 


silty sand 


3381 


3252 


1.040 


18 


F03-E0D 


Oklahoma 


HP14xll7 


19.42 


sa-si-clay 


clayey sand 


3452 


2518 


1.371 


19 


F04-E0D 


Oklahoma 


RC24"sq 


13.72 


sa-si-clay 


clayey sand 


7562 


2927 


2.584 


20 


F04-BOR 


Oklahoma 


RC24"sq 


17.01 


sa-si-clay 


clayey sand 


7562 


3412 


2.216 




N 


7 


Average 


1.529 


SD 


0.635 


GOV 


0.415 




P=2.33 


0.675 


3=3.0 


0.498 



Table C-10 Oklahoma CAPWAP (EOD-i-BO 


R) Data 


No 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


189 


33P1-EOD 


Ontario 


HP 12x74 


34.87 


cl-sa-silt 


silty sand 


3559 


1953 


1.822 


190 


33P1-BOR 


Ontario 


HP 12x74 


34.87 


cl-sa-silt 


silty sand 


3559 


3180 


1.119 


191 


33P1-BOR 


Ontario 


HP 12x74 


34.87 


cl-sa-silt 


silty sand 


3559 


2891 


1.231 


192 


33P2-EOD 


Ontario 


CP 12.75" 


32.67 


cl-sa-silt 


silty sand 


2180 


1290 


1.690 


193 


33P2-BOR 


Ontario 


CP 12.75" 


32.67 


cl-sa-silt 


silty sand 


2180 


1579 


1.381 


194 


33P2-BOR 


Ontario 


CP 12.75" 


32.67 


cl-sa-silt 


silty sand 


2180 


1784 


1.222 


195 


33P4-EOD 


Ontario 


PSC 12"sq 


16.52 


cl-sa-silt 


cl-silt-till 


2073 


1779 


1.165 


196 


33P5-EOD 


Ontario 


#14 Timber 


8.66 


cl-sa-silt 


cl-silt-till 


730 


636 


1.148 


197 


TRD22-EOD 


Ontario 


HP 12x74 


6.13 


sand 


till 


1575 


1922 


0.819 


198 


TRD22-BOR 


Ontario 


HP 12x74 


6.13 


sand 


till 


1575 


1308 


1.204 


199 


TRE22-EOD 


Ontario 


HP 12x74 


7.83 


sand 


rock 


2473 


2558 


0.967 


200 


TRE22-BOR 


Ontario 


HP 12x74 


7.83 


sand 


rock 


2473 


2740 


0.903 


201 


TRP5X-EOD 


Ontario 


HP 12x53 


7.68 


sand 


rock 


1824 


2153 


0.847 


202 


TRP5X-BOR 


Ontario 


HP 12x53 


7.68 


sand 


rock 


1824 


1757 


1.038 


203 


TR131-BOR 


Ontario 


CP 7.063" 


NA 


sand 


rock 


623 


738 


0.844 




N 


15 


Average 


1.160 


SD 


0.294 


( 


:ov 


0.254 




p=2.33 


0.715 


P=3.0 


0.573 



255 



Table C-1 1 Pennsylvania CAPWAP (EOD+BOR) Data 



No 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 


CAPWAP 
IbrWAr 


Rdavisson 
Rcapwap 


Side 


Tip 


61 


FP5-EOD 


Penn. 


IVTonotnhp 


7.19 


odiiLiy ^1 V 1 


QnnH\7 trrvl 
fttiiiuy ^1 VI 


1081 


934 


1.157 


62 


FP5-BOR 


Penn. 


Monotube 


7.25 


adiii-i^ ^1 V 1 


<;nnH\7 trrvl 


1081 


1063 


1.017 


98 


63S-BOR 


Penn. 


HP! 2x53 


20.12 


c QtiH -C1I f 




1263 


1241 


1.018 


128 


GF19-EOD 


Psh PA 


HP10x42 


15.09 


(Tn^l - ctiH-clt 
gl VI aiiu all 


shale 


1468 


1770 


0.829 


129 


GFl 10-EOD 


Psh PA 


HPl 2x74 


15.15 


OTvl-QnH-Qlt 


shale 


2224 


2033 


1.094 


130 


GF222-EOD 


Psh PA 

A 511- A r-i. 


HP 12x74 


18.62 


or vl - n H - 1 1 


shale 


2580 


nil 


1.133 


131 


GF224-EOD 


Psh PA 


Monotube 


9.02 


grvl-snd-slt 


grvl-snd-slt 


NA 


1864 




132 


GF312-EOD 


Pgh. PA 


HP12x74 


8.6 


snd-grvl-shl 


shale 


1512 


1802 


0.839 


133 


GF313-EOD 


Pgh. PA 


HP10x57 


9.6 


snd-grvl-shl 


claystone 


1486 


1984 


0.749 


134 


GF412-EOD 


Pgh. PA 


HP12x74 


10.24 


grvl-snd-slt 


claystone 


1068 


2024 


0.528 


135 


GF413-EOD 


Pgh. PA 


HP10x57 


10.55 


grvl-snd-slt 


claystone 


1334 


1904 


0.701 


136 


GF414-EOD 


Pgh. PA 


HPIOx57 


10.58 


grvl-snd-slt 


claystone 


1601 


2331 


0.687 


137 


GF415-EOD 


Pgh. PA 


HP12x74 


10.39 


grvl-snd-slt 


claystone 


2046 


2495 


0.820 




N 


12 


Average 


0.881 


SD 


0.201 


GOV 


0.228 




3=2.33 


0.570 


p=3.0 


0.462 



Table C-12 Wisconsin CAPWAP (EQD-i-BQR) Data 



No 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 
(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


207 


CHAT-EOD 


Wisconsin 


CEP 12.75" 


37.49 


sa-si clay 


silty sand 


2909 


1735 


1.677 


208 


CHAT-BORl 


Wisconsin 


CEP 12.75" 


37.52 


sa-si clay 


silty sand 


2909 


2068 


1.407 


209 


CHA1-BOR2 


Wisconsin 


CEP 12.75" 


37.52 


sa-si clay 


silty sand 


2909 


2304 


1.263 


210 


CHA4-EOD 


Wisconsin 


CEP 12.75" 


35.66 


sa-si clay 


silty sand 


2251 


1205 


1.868 


211 


CHB2-EOD 


Wisconsin 


HP12x63 


47.34 


sa-si clay 


silty sand 


1343 


489 


2.746 


212 


CHB2-BOR1 


Wisconsin 


HP12x63 


47.34 


sa-si clay 


silty sand 


1343 


1201 


1.118 


213 


CHB2-BOR3 


Wisconsin 


HP12x63 


47.4 


sa-si clay 


silty sand 


1343 


1512 


0.888 


214 


CHB2-BOR4 


Wisconsin 


HP12x63 


47.43 


sa-si clay 


silty sand 


1343 


2002 


0.671 


215 


CHB2-BOR5a 


Wisconsin 


HPl 2x63 


47.46 


sa-si clay 


silty sand 


1343 


2291 


0.586 


216 


CHB2-BOR5b 


Wisconsin 


HPl 2x63 


47.46 


sa-si clay 


silty sand 


1343 


2126 


0.632 


217 


CHB3-EOD 


Wisconsin 


HPl 2x63 


43.31 


sa-si clay 


silty sand 


890 


467 


1.906 


218 


CHB3-BOR1 


Wisconsin 


HPl 2x63 


43.31 


sa-si clay 


silty sand 


890 


1045 


0.852 


219 


CHB3-BOR2 


Wisconsin 


HP12x63 


43.43 


sa-si clay 


silty sand 


890 


979 


0.909 


220 


CHB3-BOR3 


Wisconsin 


HP12x63 


43.53 


sa-si clay 


silty sand 


890 


1490 


0.597 


221 


CHC3-EOD 


Wisconsin 


CEP 14" 


47.3 


sa-si clay 


silty sand 


836 


489 


1.710 


222 


CHC3-BOR 


Wisconsin 


CEP14" 


47.3 


sa-si clay 


silty sand 


836 






223 


CHC3-BORL 


Wisconsin 


CEP14" 


47.34 


sa-si clay 


silty sand 


836 


1735 


0.482 


224 


CH4-EOD 


Wisconsin 


CEP9.63" 


43.43 


silty clay 




1601 


667 


2.400 


225 


CH4-BOR 


Wisconsin 


CEP9.63" 


43.43 


silty clay 




1601 


1512 


1.059 


226 


CH39-EOD 


Wisconsin 


CEP9.63" 


43.28 


silty clay 


silty clay 


2936 


832 


3.529 



256 



Table C 12 (cont.) 



Ill 


V I K ' V I > V / 1\ 


VV iSOOllolll 






ollly OlaV 


Silly OlaV 










V IK'V I>V/I\1, 


W/ 1 c r-i^n c 1 n 
VV ISOOllolll 






ollly OlaV 


CI Cl Q \7 




9SSS 
Jo 


1 MS 






VV ISi^UIIalll 






cilt\? r'lnx? 


cilt\? cnnH 

allLV lIicIIILI 








230 


CH6-5B-BOR 


Wisconsin 


CEP9.63" 


43.89 


silty clay 


silty sand 


1673 


1 77Q 

L 1 1 y 




231 


CH95B-EOD 


Wisconsin 


CEP9.63" 


42.37 


silty clay 


sand & grvl 


2473 


yoj 


Z.J iU 


232 


CH95B-BOR 


Wisconsin 


CEP9.63" 


42.37 


silty clay 


sand & grvl 


2473 


9^S8 


1 O/IQ 


233 


CH256-BOR3 


Wisconsin 


CEP9.63" 


42.67 


si-sa clay 


si-sa & grvl 


2651 


979/L 


1 1 Q9 
1 . i 7Z 


234 


CH351-BOR2 


Wisconsin 


CEP9.63" 


47.55 


si-sa clay 


si-sa & grvl 


2669 


2358 


1.132 


346 


CHI1-42-BOR1 


Wisconsin 


CEP 12.75" 


28.99 


sa-cl-silt 


silty clay 


1948 


2349 


0.829 




N 


27 


Average 


1.353 


SD 


0.742 


COV 


0.548 




p=2.33 


0.446 


|3=3.0 


0.307 



Table C-13 Canada CAPWAl 


3 (EOD-l-BOR) Data 


No 


Pile-Case 
Number 


Refer. 
No. 


Location 


Pile 
Type 


Depth 
(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


91 


35-1-BOR 


C.N.R. 


Toronto 


HP12x74 


14.78 


cl-sa-silt 


silty sand 


1432 


1157 


1.238 


92 


35-4-BOR 


C.N.R. 


Toronto 


CEP12.75" 


14.69 


cl-sa-silt 


silty sand 


1468 


1601 


0.917 


93 


35-5-BOR 


C.N.R. 


Toronto 


HP12x74 


27.58 


cl-sa-silt 


silty sand 


2722 


2891 


0.942 


94 


35-6-BOR 


C.N.R. 


Toronto 


CEP12.75" 


27.43 


cl-sa-silt 


silty sand 


2669 


2580 


1.034 


95 


35-7-BOR 


C.N.R. 


Toronto 


T. Timber 


12.68 


cl-sa-silt 


silty sand 


543 


618 


0.879 


96 


35-10-BOR 


C.N.R. 


Toronto 


PSC 12"sq 


14.63 


cl-sa-silt 


silty sand 


1788 


1486 


1.203 


138 


EF62-EOD 


Ottawa 


Canada 


CP 9.625" 


18.99 


si-sa-clay 


till 


2233 


2322 


0.962 


139 


EF167-BOR 


Ottawa 


Canada 


CP 9.625" 


21 


si-sa-clay 


till 


1205 


2131 


0.565 




N 


8 


Average 


0.967 


SD 


0.209 


< 




0.216 




p=2.0 


0.640 


P=2.5 


0.521 



257 





fable C-14 Alabama CAPWAP (BOR) Data 


No. 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 
(m) 


Soil Type 


Davisson's 
Criteria 


CAPWAP 
ItrW Ar 


Rdavisson 
Rcapwap 


Side 


Tin 
lip 








PSr 18"sn 


19 66 


cilt\? cnnH 


alliy ^clllu 


1646 


1 143 


1.440 


A 7 


FAT ROT? 9 


rVldUallla 


pep 1 8"cn 


1 Q 7S 


siiiy sdiiu 


Silly SdllU 


iOH-D 


low 




A ^ 


FA? RORT 


A 1 Q m Q 

/\laUailia 


P^nP 1 S"Qn 
rov^ lo SL| 




silty sand 


silty sand 




7 1 7S 

Z, 1 / J 


1 1 9S 

1 . 1 Z,J 


/l A 
40 


FA2-BOR2 


Alabama 


PSC 18"sq 


23.01 


silty sand 


silty sand 


2447 


ZDDt- 


n Q1 Q 


48 


FA3-BORI 


Alabama 


PSC 24"sq 


19.54 


silty sand 


silty sand 


2780 


1 JDD 




49 


FA3-BOR2 


Alabama 


PSC 24"sq 


19.66 


silty sand 


silty sand 


2780 


Z,U 1 1 


1 OfiS 
1 .wuj 


51 


FA4-BOR1 


Alabama 


PSC 24"sq 


22.89 


silty sand 


silty sand 


3634 


zuo / 


1 ^S9 


52 


FA4-BOR2 


Alabama 


PSC 24"sq 


22.92 


silty sand 


silty sand 


3634 


3790 




54 


FA5-BOR 


Alabama 


PSC 36"sq 


22.28 


silty sand 


silty sand 


5071 


4204 


1.206 




N 


9 


Average 


1.230 


SD 


0.351 


GOV 


0.285 




p=2.33 


0.713 


P=3.0 


0.562 



Table C-15 Florida CAPWAP (BOR) Data 



No. 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 
(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


IXLlaVlaaUll 

Rcapwap 


Side 


Tip 


79 


WC3-BORI 


Florida 


PSC24"sq 


8.38 


Is. -d. sand 


dense 


2713 


2251 


1.205 


80 


WC3-BOR2 


Florida 


PSC24"sq 


8.38 


Is: d.sand 


dense 


2713 


2384 


1.138 


82 


WC6-BOR1 


Florida 


PSC24"sq 


8.69 


Is. -d. sand 


dense 


2015 


2135 


0.944 


83 


WC6-BOR2 


Florida 


PSC24"sq 


8.38 


Is. -d.sand 


dense 


2015 


1971 


1.022 


84 


WB9-BOR 


Florida 


PSC30"sq 


39.17 


clayey sand 


clayey 


4003 


4186 


0.956 


85 


WB15-BOR 


Florida 


PSC30"sq 


31.58 


sand 


silt-clay 


3648 


3581 


1.019 


141 


A3-BOR2 


Florida 


VC 24"sq 


27.55 


clayey sand 


sand 


4261 


2055 


2.073 


142 


A3-BOR3 


Florida 


VC 24"sq 


27.61 


clayey sand 


clayey sand 


4261 


4115 


1.035 


145 


A14-BOR1 


Florida 


VC 24"sq 


17.83 


clayey sand 


sand 




2687 




146 


A14-BOR2 


Florida 


VC 24"sq 


17.92 


clayey sand 


sand 




4279 




148 


A25-BOR1 


Florida 


VC 24"sq 


16.82 


clayey sand 


sand 


3180 


2469 


1.288 


149 


A25-BOR2 


Florida 


VC 24"sq 


16.89 


clayey sand 


sand 


3180 


2011 


1.581 


150 


A25-BOR3 


Florida 


VC 24"sq 


16.92 


clayey sand 


sand 


3180 


1966 


1.617 


152 


A16-BOR1 


Florida 


PSC18"sq 


18.47 


sandy clay 


sand 


1401 


1254 


1.117 


153 


A16-BOR2 


Florida 


PSC18"sq 


18.59 


sandy clay 


sand 


1401 


1317 


1.064 


155 


A41-BOR1 


Florida 


VC 24"sq 


15.85 


clay 


sand 


2331 


2237 


1.042 


156 


A41-BOR2 


Florida 


VC 24"sq 


16.09 


clay 


sand 


2331 


2513 


0.928 


158 


AlOl-BORI 


Florida 


VC 24"sq 


18.84 


clay 


clayey sand 


3612 


2976 


1.214 


159 


A101-BOR2 


Florida 


VC 24"sq 


18.93 


clay 


clayey sand 


3612 


3572 


1.011 


161 


A133-BOR 


Florida 


VC 24"sq 


31.97 


clayey sand 


sandy clay 


3594 


3470 


1.036 


163 


A145-BOR1 


Florida 


VC 24"sq 


31.36 


clayey sand 


sand 


4341 


2851 


1.523 


164 


A145-BOR2 


Florida 


VC 24"sq 


31.39 


clayey sand 


sand 


4341 


3385 


1.282 


165 


CB3-BOR 


Florida 


PSC24"sq 


23.47 


clayey sand 


sand 


2224 


2509 


0.886 


166 


CB3-BORL 


Florida 


PSC24"sq 


23.71 


clayey sand 


sand 


2224 


2233 


0.996 



258 



Table C- 15 (cont.) 



1 fn 
10/ 




rioriud 


V j\j st| 


ID. 10 


Clayey adllU 


sand 




ZjZ / 


9 900 


lOo 




Florida 


V \^ j\j sq 




clayey sand 


sandy clay 




ZjVo 


9 1A0 
Z. 14U 




r'R 1 1 ROPT 


Florida 


V \^ j\j sq 


ZO. IZ 


clayey sand 


clayey sand 


fy'\9'~K 


jOZI 


1 . /03 


1 /U 


r^R 1 1 POPT 


Florida 


vi^ jU sq 


9A 1 ^ 
ZO. 1 J 


clayey sand 


clayey sand 


(^'X9'X 
DJOJ 


Zo4Z 


9 9/lA 
Z.Z40 


1 / i 


r'R 1 7 ROP 1 


Florida 


j\j sq 


9'? 


clayey sand 


clayey sand 


/ 


j04o 


1 9A1 
1 .o4 / 


1 79 


r'R 1 7 ROP9 


Florida 


vi^ j\j sq 


9'? 71 
Zj. / 1 


clayey sand 


clayey sand 


/ jV 




9 09 
Z.UZ3 


1 7'^ 


r'R 1 7 ROPT 


Florida 


V \^ j\) sq 


9'? 7zl 

Zj. /H- 


clayey sand 


clayey sand 


/ jV 


'\C\'X9 

J\JJO 


9 918 
Z.Z 1 


1 lA 


r^R 1 7 FvPT 


Florida 


vi^ jU sq 


97 C/1 


clayey sand 


clayey sand 


A7'iQ 
/ 


J Ijy 


1 707 
i . / V3 


1 7^ 
1/3 


f^ROT ROP 


Florida 


V \^ j\j sq 


9A AS 


clayey sand 


sand 


ZoOU 


Z / J J 


1 .Kjjy 


1 /O 


/"^ROO ROPF 


Florida 


vi^ju sq 


9^ 91 
ZJ.Z i 


clayey sand 


sand 


ZoOU 


1 Q7^ 

ly ID 


1 AA9 
1 .44o 


1 77 
ill 


/~^R9Q ROPT 


Florida 


V \^ j\j sq 


9^ lf\ 
Zj. /O 


clayey sand 


clayey sand 


/y 


043 Z 


1 1 91 
1 . 1 oZ 


1 7G 
I/O 


r^R'lQ POPT 
l^r> Z V-iiUKL 


Florida 


\/r" 'iM"c/n 

vi^ jU sq 


9^ 7 A 
Zj. /O 


clayey sand 


clayey sand 


ACTIOS 


1 QQ7 

Vyy 1 


9 O/l 7 
Z.U43 


1 7Q 

1 /y 


/"^RQ^ ROP 1 


Florida 


vr" "^o'^n 
j\j sq 


9'? Q"? 


clayey sand 


clayey sand 


f\^f\9 
ODVo 


jOIZ 


1 809 
1 .oUZ 




f^RQ^ ROP9 


Florida 


vr" "^o'^n 
j\j sq 


9A 0^ 


clayey sand 


clayey sand 


f\^f\9 
ODVo 


zL99 1 
4ZZ1 


1 ^A9 
1 .34Z 


loi 


/"^RQ^ ROPT 


Florida 


V \^ j\) sq 


9A 1 1 
Z^. 1 i 


clayey sand 


clayey sand 


OjUo 


4U4j 


1 AT 
1 .OIU 


1 C9 

loz 


r^R/1 1 POP 


Florida 


\/r" 7n"c^ 
vi^ jU sq 


1 Q 79 


sandy clay 


sandy clay 


OZ /Z 


JolZ 


1 .043 


1 R'^ 


r^R/ii ROP 


Florida 


vr" '?n"cn 
V \^ j\j sq 


1 Q 79 


sandy clay 


sandy clay 


OZ / Z 




1 .03y 


1 9.A 
1 oH- 


r'RAI ROPT 


Florida 


vr" '?n"on 
V sq 




sandy clay 


sandy clay 


OZ / Z 


9 1 ^7 

Z 13 / 


9 Q08 


loO 


C^lf\ ROP 


Florida 


roVw-ZH- sq 


iV.Uo 


clayey sand 


sand 


H-Z l\j 


Z / 33 


1 ^^1 
1 .331 


1 C7 
15/ 


r'R'lA POP 


Florida 


ro<^/4 sq 


1 Q 7^ 


clayey sand 


sandy clay 


4Z /U 


1. 1 9^ 
3 lo3 


1 1.A 1 
1 .341 


loo 


r'R'^A ROP9 


Florida 


roi^Z^ sq 


1 Q 8 1 


sandy clay 


sandy clay 


HZ l\) 


Z3U4 


1 70^ 
1 . /U3 




P09 ROP 1 


Florida 


ro^lo sq 


J. 1 J 


sand 


dense sand 


1910 
IZ ly 


1 ^^9 
133Z 


Q09 


ZjO 


P09 ROP9 


Florida 


ro^lo sq 


A 07 


sand 


dense sand 


1910 
IZ ly 


1 1 lA 
11/4 


1 .U3o 


Z J / 


ROPT 


Florida 


DQr" 1 C"c^ 
rol^lo sq 


A 98 
O.Zo 


sand 


dense sand 


iZiV 


1 9^n 

1Z3U 


Q7^ 

u.y /3 


Z.JO 


P0 1 Q ROP 


Florida 


roi-^lo sq 




sand 


dense sand 


lUZj 


1 ^^A 
1334 


7A7 

u. /o/ 




POI Q FOPT 


Florida 


per"! Q"r,n 


^ "^A 


sand 


dense sand 


lUZj 


1U43 


Q7Q 
yj.y ly 


Z^i 


pp-^ ROPI 


Florida 


ro^^Z^ sq 


9^ 07 


sand 


sand 




9Q97 
ZVZ / 


1 9QQ 
1 .ZW 


1A 1 
Z4Z 


PP^ ROPO 


Florida 


PQr"'7/I "c/n 

ro<^Z4 sq 


9A (\X 
ZO.Uj 


sand 


sand 




A 1 9'^ 
41Z3 


Q99 


Z'+j 


PP^ ROPT 


Florida 


roi^Z^ sq 


9A 1 ^ 
ZO. 1 J 


sand 


sand 


J ok) J 


9A1 1 
ZOl 1 


1 zL^7 
1 .43 / 


Z'4-^ 


PP77 ROP 


Florida 


ro^ZH sq 


1 8 ^A 
io.JO 


clayey sand 


cl-si-sand 


7zL'^'^ 


3303 


9 910 
Z.ZIU 


Z-^-j 


PP77 ROPT 


Florida 


p<;r"9zi"cn 
ro^ZH sq 


1 8 A8 
io.Oo 


clayey sand 


cl-si-sand 




AA9A 
44 o4 


1 f\^9 
1 .03 


0/17 
Z4 / 


RR 1 'i ROP 1 n 


Florida 


vi^ jU sq 


98 'i9 
ZO. jZ 


clayey sand 


sand 


AAI^ 
44 / J 


4uyz 


1 OQ/1 
1 .UV4 


Z^O 


RR 1 ROPTh 


Florida 


vr" '?n"on 
V \^ j\j sq 


98 '?9 
Zo. jZ 


clayey sand 


sand 


44 / D 


jyjy 


1 1 '^0 
1 . 13U 


z^y 


RR 1 ROP^-a 


Florida 


vr" '?n"on 
j\j sq 


98 71 
Zo. / 1 


clayey sand 


sand 


44 / J 


4 /OU 


QzLO 


Z3U 


RR1 ROP9K 
1313 1 j-rSvJKZD 


Florida 


vr" '?n"cn 
V \^ j\j sq 


98 71 
Zo. / 1 


clayey sand 


sand 


44 / J 


40 / 1 




U.V3o 


z J 1 


RR T'^ ROPT 
1313 lJ-13vJlvL. 




VP ^n"Qn 

V j\j sq 


98 8 
zo.o 


r^tn^T p^^i con/1 

Clayey sdiiu 


sand 


44 / D 


4UW0 


1117 
1.11/ 


252 


RRl Q-RORa 


Flondti 


Vr 30"sn 


27.13 


sand 


sand 


^ 1 yjy 




1.244 






Flondci 


Vr 30"sn 


27.13 


sand 


sand 


S169 

^ 1 yjy 


4666 


1 108 




RRIQ-RORT 


Flondti 


Vr 30"sn 


27.19 


sand 


sand 


SI 69 


651 ? 


794 


256 


BB24-BORla 


Florida 


VC 30"sq 


24.48 


sand 


clay 


4955 


7517 


0.659 


257 


BB24-BORIb 


Florida 


VC 30"sq 


24.48 


sand 


clay 


4955 


7571 


0.654 


258 


BB24-BOR2a 


Florida 


VC 30"sq 


24.63 


sand 


clay 


4955 


8420 


0.588 


259 


I31324-BOR2b 


Florida 


VC 30"sq 


24.63 


sand 


clay 


4955 


7873 


0.629 


260 


BB24-BORL 


Florida 


VC 30"sq 


24.69 


sand 


clay 


4955 


6241 


0.794 


261 


BB29-BOR 


Florida 


VC 30"sq 


23.90 - 


sand 


sand 


5053 


5458 


0.926 


262 


BB29-BORL 


Florida 


VC 30"sq 


23.96 


sand 


sand 


5053 


5115 


0.988 



259 



Table C- 15 (cont.) 





ARF6-RnR 


Fl on H ?i 


PSr 24" sn 


17.54 






3345 


1677 


1 995 


264 


ARF6-RnRT 


Fl r\ri H n 


PSr 24" sn 


17.84 




^.itiycy dciiiu 


3345 


3474 


963 




ARni ^ RORT 




P^sP 7/1" cn 


1 A OS 


Clayey ;^aiiu 


IIIIICl^LOIIC 


47/19 






zoo 


ABHz-bvJK 


rlorida 


r^C z4 sq 


io.y 


silt/silty clay 


limestone 


Z5l5 


3j94 


0. /Ol 


OAT 

zo / 




Florida 


roC z4 sq 


iU.vO 


silt/silty clay 


limestone 


1 

ZOio 


/ir\oo 

4uyz 


U.Oi J 


375 


UFSSIA - BOR 


Florida 


PSC 24" sq 


15 


cl-si-sand 


silty clay 


3496 


5427 


0.644 


376 


UPS SIB - BOR 


Florida 


PSC 20" sq 


14.42 


cl-si-sand 


silty clay 


2611 


3554 


0.735 


377 


UFSS I O - BOR 


Florida 


PSC 24" sq 


8.5 


sa-si-clay 


silty clay 


5107 


6228 


0.820 


378 


UFSS13B - BOR 


Florida 


PSC 24" sq 


8.2 


sa-si-clay 


silty clay 


2771 


4226 


0.656 


379 


BIT20 - BOR 


Florida 


PSC 20" sq 


14.08 


silty sand 


sand 


2593 


2108 


1.230 


380 


BIT21 - BOR 


Florida 


PSC 20" sq 


11.09 


cl-si-sand 


silty sand 


1637 


1606 


1.019 


383 


HFLS4L - BOR 


Florida 


PSC 30" sq 


22.4 


cl-si- 
limestone- 
sand 


limerock 


3354 


A(Mf\ 




384 


RBA30 - BOR 


Florida 


PSC 30" sq 


16.28 


silty sand 


silty sand 


4039 


ODVZ 


i .UV4 


385 


RBB30W - BOR 


Florida 


PSC 30" sq 


13.35 


silty sand 


silty sand 


3461 


dLLj 


1 (YTX 


386 


CC6 - BOR 


Florida 


PSC 18" sq 


16.18 


silty sand 


sand 


1388 


1423 


u.y / J 


387 


CC7 - BOR 


Florida 


PSC 14" sq 


23.23 


cl-si-sand 


silty sand 


1770 


1810 


n 078 


388 


CC14-BOR 


Florida 


PSC 14" sq 


21.18 


cl-si-sand 


silty sand 


1601 


1890 


847 




N 


85 


Average 


1.243 


SD 


0.475 


( 


:ov 


0.382 




3=2.33 


0.589 


p=3.0 


0.442 



able C-16 Kenner, LA CAPWAP (BOR) Data 



No. 


Pile -Case 
Number 


Location 


Pile 
Type 


Penetr 
Depth (m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


292 


LB3-BOR1 


Kenner, LA 


PSC 24" sq 


24.99 


clay 


Sand 


1842 


912 


2.020 


293 


LB3-BOR2 


Kenner, LA 


PSC 24" sq 


24.99 


clay 


Sand 


1842 


1534 


1.201 


294 


LB3-BOR3 


Kenner, LA 


PSC 24" sq 


24.99 


clay 


Sand 


1842 


1677 


1.098 


296 


LB4-BOR1 


Kenner, LA 


PSC 30" sq 


25.21 


clay 


Sand 


2273 


887 


2.563 


297 


LB4-BOR2 


Kenner, LA 


PSC 30" sq 


25.27 


clay 


Sand 


2273 


1299 


1.750 


298 


LB4-BOR3 


Kenner, LA 


PSC 30" sq 


25.3 


clay 


Sand 


2273 


1521 


1.494 


299 


LB4-BOR4 


Kenner, LA 


PSC 30" sq 


25.3 


clay 


Sand 


2273 


1603 


1.418 


301 


LB5-BOR1 


Kenner, LA 


PSC 30" sq 


24.99 


clay 


Sand 




952 




302 


LB5-BOR2 


Kenner, LA 


PSC 30" sq 


24.99 


clay 


Sand 




1402 




303 


LB5-BOR3 


Kenner, LA 


PSC 30" sq 


25.3 


clay 


Sand 




1591 




304 


LB5-BOR4 


Kenner, LA 


PSC 30" sq 


25.3 


clay 


Sand 




1752 




306 


LB6-BOR1 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2411 


883 


2.730 


307 


LB6-BOR2 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2411 


1322 


1.824 


308 


LB6-BOR3 


Kenner, LA 


PSC 36" cyl 


24.99 


clay 


Sand 


2411 


1767 


1.364 


309 


LB6-BOR4 


Kenner, LA 


PSC 36" cyl 


24.99 


clay 


Sand 


2411 


2300 


1.048 


311 


LB7-BOR1 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


875 


2.745 



260 



Table C- 16 (cont.) 



312 


LB7-BOR2 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


1 77Q 


1 R7R 
i .o / o 


313 


LB7-BOR3 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


1891 


1 770 


314 


LB7-BOR4 


Kenner, LA 


PSC 36" cyl 


24.69 


clay 


Sand 


2402 


2260 


1.063 




N 


15 


Average 


1.698 


SD 


0.592 


COV 


0.349 




P=2.33 


0.863 


p=3.0 


0.659 



Table C-17 Ontario CAPWAP (BOR) 1 


Data 


No. 


Pile-Case 
Number 


Refer. 
No. 


Location 


Pile 
Type 


Depth 
(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


190 


33P1-BOR 


SiteP 


Ontario 


HP 12x74 


34.87 


cl-sa-silt 


silty sand 


3559 


3180 


1.119 


191 


33P1-EOR 


SiteP 


Ontario 


HP 12x74 


34.87 


cl-sa-silt 


silty sand 


3559 


2891 


1.231 


193 


33P2-BOR 


SiteP 


Ontario 


CP 12.75" 


32.67 


cl-sa-silt 


silty sand 


2180 


1579 


1.381 


194 


33P2-EOR 


SiteP 


Ontario 


CP 12.75" 


32.67 


cl-sa-silt 


silty sand 


2180 


1784 


1.222 


198 


TRD22-BOR 


SiteR 


Ontario 


HP 12x74 


6.13 


sand 


till 


1575 


1308 


1.204 


200 


TRE22-BOR 


SiteR 


Ontario 


HP 12x74 


7.83 


sand 


rock 


2473 


2740 


0.903 


202 


TRP5X-BOR 


SiteR 


Ontario 


HP 12x53 


7.68 


sand 


rock 


1824 


1757 


1.038 


203 


TR131-BOR 


SiteR 


Ontario 


CP 7.063" 


NA 


sand 


rock 


623 


738 


0.844 




N 


8 


Average 


1.118 


SD 


0.180 


COV 


0.161 




p=2.33 


0.809 


p=3.0 


0.675 



able C-18 S.Carolina CAPWAP (BOR) Data 



No 


Pile-Case 
Number 


Location 


Pile 
Type 


Penetr 
Depth 

(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


269 


BC79-BORL 


S.Carolina 


PSC 24" oct 


23.5 


si-cl-sand 


calcar sand 


2277 


2447 


0.931 


271 


BC64-BORL 


S.Carolina 


PSC 24" oct 


18.62 


si-cl-sand 


calcar sand 


5071 


5004 


1.013 


279 


MB 1 -BOR 


S. Carolina 


PSC 16"sq 


19.2 


sand 


silty sand 


3590 


2326 


1.543 


280 


MB2-BOR 


S. Carolina 


HP14x89 


20.12 


silty sand 


calcar. silt 


3990 


2362 


1.689 


281 


MB3-BOR 


S. Carolina 


OEP 16" 


20.12 


silty sand 


calcar. silt 


4146 


2540 


1.632 


283 


SI-BOR 


S. Carolina 


OEP 24" 


24.84 


clayey sand 


sandy silt 


2651 


2687 


0.987 


285 


S2-BOR 


S. Carolina 


HP14x73 


23.77 


clayey sand 


sandy silt 


1415 


1366 


1.036 


331 


DWI-BORl 


S. Carolina 


PSC 24" sq 


27.46 


silty clay 


silty clay 


4742 


4515 


1.050 


332 


DW 1-BOR2 


S. Carolina 


PSC 24" sq 


27.52 


silty clay 


silty clay 


4742 


5178 


0.916 


333 


DW2-BORI 


S. Carolina 


HP14X73 


27.46 


si-sa-clay 


silty clay 


2753 


2798 


0.984 


334 


DW2-BOR2 


S. Carolina 


HP 14X73 


27.52 


si-sa-clay 


silty clay 


2753 


3025 


0.910 



261 



Table C- 18 (cont.) 



335 


DSl-BORI 


S. Carolina 


PSC 12" sq 


26.82 


cl-si-sand 


calcar sand 


1601 


1214 


1.319 


336 


DS1-BOR2 


S. Carolina 


PSC 12" sq 


26.85 


cl-si-sand 


calcar sand 


1601 




1.U43 




N 


13 


Average 


1.158 


SD 


0.285 


GOV 


0.246 


$ P=2.33 
p=3.0 


0.703 
0.565 



Table C-19 Wisconsin CA 



'WAP (BQR) Data 



No. 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 
(m) 


Soil Type 


Davisson's 
Criteria 


CAPWAP 
IbrWAr 


Rdavisson 
Rcapwap 


oiae 


lip 


908 




VV lOl^UIIOlII 




J 1 — IjL 


sa-si clay 


silty sand 






1 4.07 


209 






CFP 12 75" 


37.52 


sa-si clay 


silty sand 


2909 


2304 


1.263 


212 


CHB2-BOR1 


Wisconsin 


HP12x63 


47.34 


sa-si clay 


silty sand 


1343 


1201 


1.118 


213 


CHB2-BOR3 


Wisconsin 


HP12x63 


47.4 


sa-si clay 


silty sand 


1343 




888 
Vj. ooo 


214 


CHB2-BOR4 


Wisconsin 


HP12x63 


47.43 


sa-si clay 


silty sand 


1343 


7009 


f^^ 


215 


CHB2-BOR5a 


Wisconsin 


HP12x63 


47.46 


sa-si clay 


silty sand 


1343 


2291 


586 

\J.UO\J 


216 


CHB2-BOR5b 


Wisconsin 


HP12x63 


47.46 


sa-si clay 


silty sand 


1343 


2126 


639 


218 


CHB3-BOR1 


Wisconsin 


HP12x63 


43.31 


sa-si clay 


silty sand 


890 


1045 


0.852 


219 


CHB3-BOR2 


Wisconsin 


HP12x63 


43.43 


sa-si clay 


silty sand 


890 


979 


0.909 


220 


CHB3-BOR3 


Wisconsin 


HP12x63 


43.53 


sa-si clay 


silty sand 


890 


1490 


0.597 


222 


CHC3-BOR 


Wisconsin 


CEP14" 


47.3 


sa-si clay 


silty sand 


836 






223 


CHC3-BORL 


Wisconsin 


CEP14" 


47.34 


sa-si clay 


silty sand 


836 


1735 


0.482 


225 


CH4-BOR 


Wisconsin 


CEP9.63" 


43.43 


silty clay 




1601 


1512 


1.059 


227 


CH39-BOR 


Wisconsin 


CEP9.63 


43.28 


silty clay 


silty clay 


2936 


2046 


1.435 


228 


CH39-BORL 


Wisconsin 


CEP9.63" 


43.37 


silty clay 


silty clay 


2936 


2558 


1.148 


230 


CH6-5B-BOR 


Wisconsin 


CEP9.63" 


43.89 


silty clay 


silty sand 


1673 


1779 


0.940 


232 


CH95B-BOR 


Wisconsin 


CEP9.63" 


42.37 


silty clay 


sand & grvl 


2473 


2358 


1.049 


233 


CH256-BOR3 


Wisconsin 


CEP9.63" 


42.67 


si-sa clay 


si-sa & grvl 


2651 


2224 


1.192 


234 


CH351-BOR2 


Wisconsin 


CEP9.63" 


47.55 


si-sa clay 


si-sa & grvl 


2669 


2358 


1.132 




N 


18 


Average 


0.964 


SD 


0.286 


( 


:ov 


0.296 




3=2.33 


0.547 


p=3.0 


0.429 



Table C-20 Florida CAPWAP (EQD) Data 



No. 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 
(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


78 


WC3-EOD 


Florida 


PSC24"sq 


8.32 


Is. -d. sand 


dense 


2713 


2264 


1.198 


81 


WC6-EOD 


Florida 


PSC24"sq 


8.63 


Is.-dsand 


dense 


2015 


2002 


1.006 


105 


STl-EOD 


Florida 


PSC 18"sq 


13.41 




carb sand 


1530 


2246 


0.681 



262 



Table C-20 (cont.) 



1 MA 


o 1 Z-n,\J\J 


Florida 


roK. io sq 


1 1 Q 
iZ. iV 




carb sand 


LLvry 


z /4U 


U.OZO 


1 /IM 




Florida 


z4 sq 


Z / . JZ 


— ; ~A — 

clayey sand 


sand 


4z01 


1 A77 


Z.OUj 


1 Al 
1^ / 




Florida 


V zH- sq 


10. /y 


clayey sand 


sand 




ZU'4-Z 


1 ^^7 

1 .J J I 


1 J 1 




Florida 


roV^io sq 


1 C /t7 


sandy clay 


sand 




QQA 


1 /in7 


1 ^/f 
1 J4 




Florida 


vi^ z4 sq 




clay 


sand 




1 Q 1 7 


1 1 A 
1 .zlO 


1 ^7 


Aim For> 


Florida 


V sq 


io.o'4 


clay 


clayey sand 




zjUU 


1 ^7n 


1 AH 




Florida 


V \^ z-H- sq 


"^1 A7 


clayey sand 


sandy clay 






z.jW 


162 


A145-EOD 


Florida 


VC 24"sq 


31.36 


clayey sand 


sand 


4341 


1570 


2.765 


185 


CB26-EOD 


Florida 


PSC24"sq 


19.05 


clayey sand 


sand 


4270 


2171 


1.967 


239 


P019-E0D 


Florida 


PSC18"sq 


5.24 


sand 


dense sand 


1023 


1090 


0.939 


246 


BB13-EOD 


Florida 


VC 30"sq 


28.29 


clayey sand 


sand 


4475 


3114 


1.437 


255 


BB24-EOD 


Florida 


VC 30"sq 


24.44 


sand 


clay 


4955 


5783 


0.857 


381 


HFLS3 - EOD 


Florida 


PSC 30" sq 


12.07 


sa-si-clay 


sandy clay 


7073 


5787 


1.222 


382 


HFLS4L - EOD 


Florida 


PSC 30" sq 


22.4 


cl-si-limestone- 
sand 


limerock 


3354 


3136 


1.070 


389 


49SB37 - EOD 


Florida 


PSC 30" sq 


7.13 


sandy clay 


Silty 
limestone 


5058 


4559 


1.109 




N 


18 


Average 


1.503 


SD 


0.650 


GOV 


0.433 




p=2.33 


0.638 


p=3.0 


0.467 





fable C-21 Massachusetts CAPWA] 


P(EOD) Data 


No. 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


115 


GZZ5-EOD 


Boston MA 


CEP 14" 


26.52 


till-clay 


till 


2064 


952 


2.168 


116 


GZ05-E0D 


Boston MA 


CEP 14" 


16.46 


till-clay 


till 


2135 


912 


2.341 


117 


GZCC5-EOD 


Boston MA 


CEP 14" 


24.38 


till-clay 


till 


2002 


2189 


0.915 


118 


GZL2-EOD 


Boston MA 


CEP 14" 


25.3 


till-clay 


till 


2847 


1188 


2.396 


119 


GZP14-EOD 


Boston MA 


CEP 14" 


18.44 


till-clay 


till 


1735 


1357 


1.279 


120 


GZPll-EOD 


Boston MA 


CEP 14" 


17.22 


till-clay 


till 


1112 


1063 


1.046 


121 


GZP12-EOD 


Boston MA 


CEP 14" 


21.03 


till-clay 


till 


2224 


2313 


0.962 


315 


DI221-EOD 


Massachusetts 


PSC 14" 


19.2 


sa-si-clay 


fine sand & silt 


1477 






317 


TW488-EOD 


Massachusetts 


PSC 14" 


23.16 


stiff clay 


stiff clay 


1423 


365 


3.899 


319 


NBTP2-EOD 


Massachusetts 


HP12X74 


34.14 


si-sa-clay 


glacial till 


1806 


1352 


1.336 


322 


NBTP3-EOD 


Massachusetts 


HP12X74 


33.07 


si-sa-clay 


silty 


2126 


1401 


1.517 


325 


NBTP5-EOD 


Massachusetts 


CEP12.75" 


33.83 


si-sa-clay 


glacial till 


1632 


1423 


1.147 




N 


11 


Average 


1.728 


SD 


0.904 


( 


cov 


0.523 




3=2.33 


0.602 


p=3.0 


0.419 



263 



able C-22 Oakland, CA CAPWAP (EOD) Data 



No. 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


S( 

Side 


3il Type 

Tip 


Davisson's 
(kN) 


A D\A7' A D 

CAr W Ar 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


356 


ODIJ-EOD 


Oakland, CA 


OEP 24" 


8.47 


silty sand 


silty clayey sand 


7722 


3496 


2.209 


357 


OD2P-EOD 


Oakland, CA 


OEP 24" 


12.19 


silty sand 


silty sandy clay 


3047 


1557 


1.957 


359 


OD2T-EOD 


Oakland, CA 


CEP 24" 


10.67 


silty sand 


silty sand & clay 


3616 


3634 


0.995 


360 


OD3H-EOD 


Oakland, CA 


OEP 42" 


30.63 


stiff clay 


clay w/ sa-si-gr 


4639 


1441 


3.219 


361 


OD4L-EOD 


Oakland, CA 


CEP 24" 


19.51 


sandy clay 


silty sandy clay 


4399 


2242 


1.962 


362 


OD4P-EOD 


Oakland, CA 


CEP 24" 


17.07 


silty clay 


silty sandy clay 


3087 


1214 


2.543 


364 


OD4T-EOD 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy clay 


3229 


1339 


2.412 


366 


OD4W-EOD 


Oakland, CA 


CEP 24" 


18.29 


sandy clay 


silty sandy clay 


3937 


1766 


2.229 




N 


8 


Average 


2.191 


SD 


0.629 


< 




0.287 





3=2.33 


1.265 


p=3.0 


0.997 



Table C-23 Ontario CAPWAP (EOD) Data 



No. 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil 
Side 


Type 
Tip 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


189 


33P1-EOD 


Ontario 


HP 12x74 


34.87 


cl-sa-silt 


silty sand 


3559 


1953 


1.822 


192 


33P2-EOD 


Ontario 


CP 12.75" 


32.67 


cl-sa-silt 


silty sand 


2180 


1290 


1.690 


195 


33P4-EOD 


Ontario 


PSC 12"sq 


16.52 


cl-sa-silt 


cl-silt-till 


2073 


1779 


1.165 


196 


33P5-EOD 


Ontario 


#14 Timber 


8.66 


cl-sa-silt 


cl-silt-till 


730 


636 


1.148 


197 


TRD22-EOD 


Ontario 


HP 12x74 


6.13 


sand 


till 


1575 


1922 


0.819 


199 


TRE22-EOD 


Ontario 


HP 12x74 


7.83 


sand 


rock 


2473 


2558 


0.967 


201 


TRP5X-EOD 


Ontario 


HP 12x53 


7.68 


sand 


rock 


1824 


2153 


0.847 




N 


7 


Average 


1.208 


SD 


0.399 


GOV 


0.330 




p=2.33 


0.639 


3=3.0 


0.493 



264 



Tab 



e C-24 Pgh. PA CAPWAP (EOD) Data 



No. 


Pile-Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davis son's 
Criteria (kN) 


CAPWAP 
IbrWAr 


Rdavisson 
Rcapwap 


oiue 


Tin 

lip 


198 




Poh PA 




1 S OQ 


grvi-siiu-siL 


shale 




1770 


89Q 




riFl lO-FOD 

VJi J- 1 Vj J— 'V^-L' 


Pgh. PA 


HP1?y74 


15 15 


grvi-siiu-siL 


shale 


2224 


2033 


1 094 






Pgh. PA 


HPl?x74 


1 8 6? 


grvi-siiu-siL 


shale 


2580 


2277 


1 133 


131 




Pgh. PA 


IVTonotiihp 

iVi. VJI IW L U. L/C 


q 0? 


grvl-snd-slt 


grvl-snd-slt 




1 864 




132 


GF312-EOD 


Pgh. PA 


HP12x74 


8.6 


snd-grvl-shl 


shale 


1512 


1 807 


yj.ojy 


133 


GF313-EOD 


Pgh. PA 


HP10x57 


9.6 


snd-grvl-shl 


claystone 


1486 




74Q 
\j. 1 ^y 


134 


GF412-EOD 


Pgh. PA 


HP12x74 


10.24 


grvl-snd-slt 


claystone 


1068 


2024 


528 


135 


GF413-EOD 


Pgh. PA 


HP10x57 


10.55 


grvl-snd-slt 


claystone 


1334 


1904 


701 


136 


GF414-EOD 


Pgh. PA 


HPIOx57 


10.58 


grvl-snd-slt 


claystone 


1601 


2331 


\J.\jO I 


137 


GF415-EOD 


Pgh. PA 


HP12x74 


10.39 


grvl-snd-slt 


claystone 


2046 


2495 


0.820 




N 


9 


Average 


0.820 


SD 


0.192 


GOV 


0.235 




3=2.33 


0.524 


P=3.0 


0.423 



Tab 



e C-25 Wisconsin CAPWAP (EOD) Data 



No. 


Pile -Case 
Number 


Location 


Pile 
Type 


Depth 

(m) 


Soil Type 


Davisson's 
Criteria 
(kN) 


CAPWAP 
TEPWAP 
(kN) 


Rdavisson 
Rcapwap 


Side 


Tip 


207 


CHAT-EOD 


Wisconsin 


CEP 12.75" 


37.49 


sa-si clay 


silty sand 


2909 


1735 


1.677 


210 


CHA4-EOD 


Wisconsin 


CEP 12.75" 


35.66 


sa-si clay 


silty sand 


2251 


1205 


1.868 


211 


CHB2-EOD 


Wisconsin 


HP12x63 


47.34 


sa-si clay 


silty sand 


1343 


489 


2.746 


217 


CHB3-EOD 


Wisconsin 


HP 12x63 


43.31 


sa-si clay 


silty sand 


890 


467 


1.906 


221 


CHC3-EOD 


Wisconsin 


CEP14" 


47.3 


sa-si clay 


silty sand 


836 


489 


1.710 


224 


CH4-EOD 


Wisconsin 


CEP9.63" 


43.43 


silty clay 




1601 


667 


2.400 


226 


CH39-EOD 


Wisconsin 


CEP9.63" 


43.28 


silty clay 


silty clay 


2936 


832 


3.529 


229 


CH6-5B-EOD 


Wisconsin 


CEP9.63" 


43.89 


silty clay 


silty sand 


1673 






231 


CH95B-EOD 


Wisconsin 


CEP9.63" 


42.37 


silty clay 


sand & grvl 


2473 


983 


2.516 




N 


8 


Average 


2.294 


SD 


0.637 


GOV 


0.278 




p=2.33 


1.349 


p=3.0 


1.068 



265 



APPENDIX D 

Calibration Resistance Factor by Using FOSM for Driven Pile 
using Static Analysis 



Table D-la Calibration Resistance Factor for Driven Pile in Cohesionless Soil 



LOCATION 


1^ 

Davisson 


^ Davisson 


Davisson 


15 

Davisson 
Schmertmann SPT 


-'^Nordlund 




Meyeihof 


SURFRIDER CONDOMINIUM-FL 


0.93 


1.11 


0.96 


0.75 


KARIDAS CONDOMINIUM #2-FL 


0.79 


0.66 


0.15 


0.48 


BEACHES OF LONGBOAT-FL 


2.54 


2.42 


0.4 


1.54 


VIENTA CONDOMINIUM-FL 


1.64 


1.68 


0.19 


0.68 


ARVIDA HOTEL-FL 


0.93 


0.95 


0.32 


0.8 


VERANDA HOTEL, SARASOTA-FL 


1.75 


1.83 


0.23 


0.9 


LONGBOAT COVE, SARASOTA-FL 


1.14 


1.18 


0.19 


0.58 


1-95 WEST PALM BEACH #1-FL 


1.11 


1.45 


0.88 


2.34 


1-95 WEST PALM BEACH #2-FL 


1.08 


1.43 


0.78 


2.05 


BLOUNT ISLAND SITE 215-FL 


1.01 


0.95 


0.7 


1.27 


BLOUNT ISLAND SITE 316-FL 


1.68 


2.56 


1.43 


2.06 


SIESTA KEY SARASOTA-FL 


2.01 


2.06 


0.27 


0.9 


ST. JOHN'S RIVER (ASCE)-3B-FL 


0.61 


0.79 


0.26 


0.77 


ST. JOHN'S RIVER (ASCE) 3C-FL 


1.06 


1.4 


0.65 


1.36 


ST. AUGUSTINE (ASCE) 4A-FL 


1.95 


1.68 


0.94 


1.69 


BLOUNT ISLAND TERM. B-20-FL 


0.6 


0.78 


0.2 


0.86 


SARASOTA MEM. HOSPITAL-FL 


1.28 


1.12 


1.37 


0.93 


PORT ORANGE BENT 2 PILE 6-FL 


0.75 


1.09 


0.53 


1.08 


BLOUNT ISLAND TERM. B-21-FL 


0.72 


0.81 


0.5 


0.83 


CAPE CANAVERAL T-6-FL 


0.69 


0.55 


0.29 


0.7 


WEST BAY BRIDGE TP15-OH 


0.42 


0.6 


1.17 


1.42 


ESCAMBIA RIVER BENT5-FL 


0.48 


0.69 


1.17 


1.68 


ROOSEVELT BRIDGE A-FL 


0.77 


0.65 


0.56 


1.52 


ROOSEVELT BRIDGE B-30-W-FL 


0.92 


0.67 


0.82 


1.89 


BUCKMAN BRIDGE TS-19-FL 


0.48 


0.7 


0.5 


1.16 


MARCO ISLAND TP2-FL 


1.59 


1.51 


0.59 


1.52 


118 GRL Piles Bailey Fork, Bailey, TN 


0.82 


0.91 


0.23 


0.78 


99 GRL Piles I-165AVater St Int, AL 


0.79 


1.01 


0.52 


1.09 


99 GRL Piles I-165AVater St Int, AL 


0.2 


0.25 


0.13 


0.37 


99 GRL Piles I-165AVater St Int, AL 


1.21 


1.53 


1.12 


2.43 


99 GRL Piles I-165AVater St Int, AL 


0.23 


0.29 


0.13 


0.35 


99 GRL Piles I-165AVater St Int, AL 


0.47 


0.66 


0.59 


0.96 


Axial Pile-Mission Avenue, Viaduct, CA 


1.93 


2.11 


1.04 


1.63 


LOAD TRANSFER #35-3, OK 


1.61 


1.62 


0.98 


2.79 


Site 35, Pile 10, Reinforced Concrete 


1.42 


1.5 


1.82 


2.32 


Jacksonville - Industrial zone # 1-FL 


0.71 


0.92 


0.48 


0.88 


Jacksonville - Industrial zone # 1-FL 










Jacksonville - Industrial # 2-FL 


0.84 


1.19 


0.61 


0.94 


Jacksonville - Industrial # 2-FL 










Number of Cases 


37 


37 


37 


37 


Average 


l.Uo 


1.1 / 


U.o4 


1.Z5 


STD deviation 


0.55 


0.56 


0.42 


0.62 


GOV 


0.52 


0.48 


0.65 


0.49 




p=2.33 


0.37 


0.45 


0.17 


0.46 


3=3.0 


0.26 


0.32 


0.11 


0.33 



266 



Table D-lb Calibration Resistance Factor for Driven Pile in Cohesionless Soil 

Using Florida Data Only 



LOCATION 


Davisson 
^ Noidlund 


Davisson 


R 

Davisson 
Meyerhof 


Davisson 
Schmeitmann SPT 






1 1 1 


u.yo 


M 7^ 
U. / J 






n AA 
u.oo 


U.l J 


U.4o 






9 /19 
Z.4Z 




1 ^/1 




1 A/1 
i .04 


1 AC 
1 .Do 


n 1 Q 
u.iy 


M AC 
U.OO 








U.JZ 


M C 
U.O 


VPPAKTT^A 140TPT <vAPA*iOTA FT 




1 


U.Zj 


u.y 


T 0XTr^T30 A T r^O\/T7 CAPAQOTA T7T 


1 1 /I 
1.14 


1 1 G 


n 1 Q 
u.iy 


n ^c 

U.JO 




1 1 1 
1.11 


1 /I ^ 


u.oo 


7/1 
Z. j4 


T Q ^ QTPAT \yrT3T7A r^U iti T7T 


1 .Uo 


1 /1 7 


U. /o 




z.Uj 


TIT OTTKTT T*iT AKTT^ ^TTF 91 ^ FT 


1 .Wl 




n 7 
u. / 


1 07 
1 .z / 


T3T OI TMT TQT A XTF* QTTTT 'i 1 A T7T 


1 AC 
1 .Do 


9 ^A 
ZOO 


1 /I 'i 

1 .4 J 


MA 
Z.UO 


CTTTQT A T^TTV Q A P A QOT A T7T 
oliio 1 A Jvtl/ 1 oAKAovJlA-rL 


Z.Ul 


9 MA 


M 07 
U.Z / 


u.y 


TMUXT'Q PT\/TTP /'AQr^TT\ l.Ti T7T 


n Ai 
u.oi 


U. /y 


r> OA 
u.zo 


M 77 
U. / / 


TOHXT'Q PTVPP f A^CV^ '^C T^T 


1 flA 

1 .uo 


1 A 


A^ 
U.03 


I 7A 
1. jO 


QT A T Tr^T TCTTXTT7 /' A Cr^T7\ /I A T7T 


1 

1 .yj 


1 AC 
1 .06 


u.y4 


1 AQ 

i.oy 


T3T MTTXTT TQT A XTF* TTTPAyf T3 1f\ T7T 


u.o 


U. / 6 


n 

U.Z 


M CA 
U.oO 


QAPACMTA \yrT7\yr UMCPTTAT T7T 


1 

1 .zo 


1 1 9 
i . iZ 


1 77 

1 . J / 


M Q7 

u.yj 


POPT OP AXrnF TIFXJT 9 PTT F A FT 


7^ 


1 no 


U. 


1 oc 
l.Uo 


T3TOITMTTQT AXTF»TTTP\yr Ti 91 17T 


n 7'7 
u. /z 


M C 1 


U.J 


M C7 
U.oj 


A PTT A XT A \/TTP AT T A T7T 
(^Arii (^AlNAViiKAL 1-0-rL 


M AQ 




M OQ 

u.zy 


M 7 

u. / 


TTQ/^AAyTPTA PT\/TTP RTTXTT^ T7T 


n /ic 


n AQ 


1 1 7 
1.1/ 


1 AC 
l.Oo 


ROOSEVELT BRIDGE A-FL 


n 77 

yj. / / 




U. Ju 


1 . JZ 


ROOSEVELT BRIDGE B-30-W-FL 


u.yz 


n A7 


n so 

u.oz 


1 8Q 

1 .oy 


RTirKMAN BRIDGE TS-1Q-FT 


48 


7 


5 


1 1fi 


MARCO ISLAND TP2-FL 


1.59 


1.51 


0.59 


1.52 


Jacksonville - Industrial zone # 1-FL 


0.71 


0.92 


0.48 


0.88 


Jacksonville - Industrial zone # 1 -EL 










Jacksonville - Industrial # 2-EL 


0.84 


1.19 


0.61 


0.94 


Jacksonville - Industrial # 2-EL 










N 

Average 
STD deviation 


27 


27 


27 


27 


1.113 


1.216 


0.591 


1.191 


0.525 


0.545 


0.358 


0.508 




COV 


0.471 


0.448 


0.606 


0.427 




|3=2.33 


0.43 


0.50 


0.17 


0.51 


3=3.0 


0.31 


0.36 


0.12 


0.38 



267 



Table D-2a Calibration Resistance Factor for Driven Pile in Cohesive Soil 



LOCATION 


T3 

Davisson 


Davisson 


R 

Davisson 


aAPI revised 


R T r 

Q'Tomhnson 


R; 

A. 


APOSTA RRTnnF PFTR H7 FT 


1 S7 


7 1 R 


1 

i .J J 


RRTnnF <\TTF ^Ozl^iA T-TinrlQ M<5 

L> \\ 1 LJK JL^ Oi i L-j ^Wt-D/\, milUS, iVio 


77 
v. / 1 




W.J J 




S? 


A 
yJ.'-T 


U.J J 


ni«t f>1 P so OS IS TPI A«rpn«irvn T A 


8fi 


77 


W.O J 


Dkf 61 P 747-01 -^Q Fast Raton T A 


64 


64 




Axial Pilp-TVTission Avpniip ViaHnr't C^A 


1.58 


1.65 


0.97 


BRIDGE SITE 1067, HINDS, MS 


0.94 


0.92 


0.59 


BRIDGE SITE 1068, HINDS, MS 


0.87 


1.64 


0.61 


BRIDGE SITE 1072A, HINDS, MS 


0.84 


0.85 


0.59 


BRIDGE SITE 3024, HINDS, MS 


0.55 


0.59 


0.36 


Dist. 02 P 7-03-40 TPS, St. Charles LA 


0.73 


0.89 


0.95 


Dist. 02 P 855-14-7 and P 855-14-5 , LA 


1.26 


1.47 


1.01 


Dist. 03 P 455-02-04 TP2, St. Landry LA 


0.8 


0.52 


0.73 


065-90-0024_and_855-04-0046_TP5-LA 


1.21 


1.08 


1.24 


494-05-0081 Ravoii Roeiif West TPI-TA 


75 


86 


73 


424-06-0005_Bayou_Boeuf_East_ Fl -LA 


0.92 


0.57 


0.95 


424-06-0005_Bayou_Boeuf_East_F2;-LA 


0.94 


0.63 


0.99 


424-06-0005_Bayou_Boeuf_East_F5-LA 


0.61 


0.38 


0.67 


424-06-0005_Bayou_Boeuf_East_F6-LA 


0.57 


0.4 


0.75 


N 

Average 
Standard deviation 
GOV 


19 


19 


19 


0.89 


0.94 


0.79 


0.31 


0.50 


0.25 


0.35 


0.54 


0.32 




p=2.33 


0.45 


0.32 


0.30 


p=3.0 


0.34 


0.22 


0.21 



268 



Table D-2b Calibration Resistance Factor for Driven Pile in Cohesive Soil 

Using Louisiana Data Only 



LOCATION 


Davisson 


Davisson 


Davisson 


ffAPI revised 


R aTomhnson 
CL 1 omlinson 


A 




5? 


4 


55 




v/.OVJ 


77 


W.O J 




64 






Dist 0? P 7-0^-40 TP^ St Charles -T A 


73 


89 


95 


Dist. 02 P 855-14-7 and P 855-14-5-LA 


1.26 


1.47 


1.01 


Dist. 03 P 455-02-04 TP2, St. Landry-LA 


0.8 


0.52 


0.73 


065-90-0024 and 855-04-0046 TP5-LA 


1.21 


1.08 


1.24 


424-05-0081_Bayou_Boeuf_West_;TPl-LA 


75 


86 


73 


424-06-0005_Bayou_Boeuf_East_ Fl -LA 


0.92 


0.57 


0.95 


424-06-0005_Bayou_Boeuf_East_F2-LA 


0.94 


0.63 


0.99 


424-06-0005_Bayou_Boeuf_East_F5-LA 


0.61 


0.38 


0.67 


424-06-0005_Bayou_Boeuf_East_F6-LA 


0.57 


0.4 


0.75 


N 

Average 
Standard deviation 


12 


12 


12 


0.818 


0.718 


0.833 


0.236 


0.322 


0.201 


( 


cov 


0.289 


0.449 


0.241 




P=2.33 


0.47 


0.29 


0.53 


p=3.0 


0.37 


0.21 


0.42 



269 



Table D-3a Calibration Resistance Factor for Driven Pile in Mixed Soil 



LOCATION 


Davisson 

D 

a Tomlinson 
Thurman 

0.97 


Davisson 

D 

a-API revised 
Thurman 

1.11 


R 

Davisson 
Thunnan 

1.03 


Davisson 

Schmertmann 
SPT 

3.58 


Davisson 

Schmeitmann 
CPT 


APP. BAY BRIDGE BENT 101 


APP. BAY BRIDGE BENT 133 


1.12 


0.72 


0.62 


2.07 




1-275 34th ST. PINELLAS-FL 


0.5 


0.55 


0.71 


0.88 




DeSOTA CONDOMINIUM MS.-FL 




1.17 


1.22 


1.16 




WASHINGTON CONDOMINIUM 




0.39 


0.46 


0.49 




SUNSHINE SKYWAY SITE 1 A-FL 








1.05 




SUNSHINE SKYWAY SITE 1 B-FL 








0.99 




SUNSHINE SKYWAY SITE 3-FL 








1.51 




SUNSHINE SKYWAY SITE 10-FL 


1.17 


0.95 


0.81 


1.88 




SUNSHINE SKYWAY SITE 13 A-FL 








2.35 




FLORENCE/MARION 3 ASD 




1.56 


1.88 


1.71 




FLORENCE / MARION 3 BSD 


0.46 


0.63 


0.6 


1.2 




FLORENCE / MARION 3 CSD 


0.45 


0.64 


0.66 


1 




NORTHEAST VILLA MIRADA - 6-FL 




1.22 


1.24 


1.71 




SEAWAY HOTELS, SAND KEY-FL 








2.68 




HOWARD FRANKLAND / LS3-FL 


0.53 


0.99 


0.85 


2.23 




CHOCTAWHATCHEE P-5-FL 




0.85 


0.99 


2.76 




CHOCTAWHATCHEE P-1 1-FL 




1.01 


1.4 


2.49 




CHOCTAWHATCHEE P-17-FL 




1.08 


1.42 


3.13 




CHOCTAWHATCHEE P-23-FL 




0.43 


0.63 


0.91 




CHOCTAWHATCHEE P-29-FL 




0.58 


0.86 


1.38 




CHOCTAWHATCHEE P-35-FL 




0.92 


1.43 


2.17 




HOWARD FRANK. / LS4 SHORT 




3.33 


3.87 


5.21 




CHOCTAWHATCHEE P-41-FL 


1.35 


1.32 


1.34 


3.52 




CHOCTAWHATCHEE FSB-26-FL 




0.38 


0.55 


1.1 




CAPE CANAVERAL T-7-FL 




0.62 


0.67 


0.96 




CAPE CANAVERAL T-14-FL 




0.9 


1.07 


1.34 




WHITE CITY BRIDGE TP3-PA 




2.56 


2.82 


3.66 




HOWARD FRANK. / LS4 LONG-FL? 








0.5 




WHITE CITY BRIDGE TP6-PA 




1.53 


1.69 


1.85 




ACOSTA BRIDGE PEIR F6-FL 




0.88 


1.01 


1.49 




ACOSTA BRIDGE PEIR G13_FL 








1.83 




BUCKMAN BRIDGE TS-13-FL 




0.42 


0.47 


1.19 




BUCKMAN BRIDGE TS-24-FL 


0.51 


0.52 


0.8 


1.07 




BUCKMAN BRIDGE TS-29-FL 




0.47 


0.61 


1.16 




APPALACHICOLA RIVER PIER14-FL 




0.76 


1.01 


1.89 




APPALACHICOLA RIVER PIER25-FL 




1.15 


1.44 


2.81 




MARINA BAY CLUB TP7-FL 








1.85 




APPALACHICOLA BAY BENT 4 1-FL 




1.51 


1.65 


3.99 




ST. MARISSA CONDO. TPS & Pile 20-FL 








1.52 





270 



Table D-3a (cont.) 



GEORGIA/FLORIDA BOUND ARY-FL 








0.76 




JACKSONVILLE SITE B-FL 








1.83 




JACKSONVILLE SITE D-FL 








1.4 




SAINT JOHN RIVER SITE F-FL 








1.09 




LONGBOAT KEY - SARASOTA-FL 


0.51 


0.75 


0.7 


0.88 




SUNSHINE SKYWAY SITE 13 B-FL 








1.37 




1 16 GRL Piles- 164/Cimaron Rvr Br, OK 


0.47 


0.76 


0.58 


1.01 




1 16 GRL Piles- 164/Cimai-on Rvr Br, OK 


0.75 


1.35 


1.06 


1.82 




119 GRL Piles-White City Bridge, FL 




1.32 


1.39 


2.51 




119 GRL Piles-White City Bridge, FL 




1.26 


1.53 


2.32 




123 GRL Piles-Dawhoo River Bridge, SC 


1.28 


1.27 


0.92 


1.59 




123 GRL Piles-Dawhoo River Bridge, SC 


0.35 


0.35 


0.29 


0.63 




124 GRL Piles-Socastee W. Way Br, SC 




0.85 


0.92 


1.41 




125 GRL Piles-Doughty St Prk Gar, SC 


1.07 


0.84 


0.76 


1.87 




126 GRL Piles-Battery Creek, SC 




0.82 


1.11 


1.73 




126 GRL Piles-Battery Creek, SC 








0.87 




204 GRL Piles-C&D Canal, Pier 17, DE 




0.64 


0.79 


1.33 




Axial Pile-Mission Avenue, Viaduct, CA 


1.36 


1.47 


1.51 


1.41 




Doheny Park Rd U.C. Sta 451H-85.5, CA 




0.4 


0.39 


0.51 




Luling Bridge; TP2-LA 


1.66 


0.65 


0.65 


2.92 




Luling Bridge; TP3; Circular void-LA 




0.79 


0.81 


6.2 




Luling Bridge; TP4; Circular void-LA 


1.72 


0.66 


0.65 


3.42 




Luling Bridge; TP5-LA 


1.84 


0.71 


0.69 


3.61 




Luling Bridge; TP6-LA 


1.74 


0.71 


0.69 


3.59 




Luling Bridge; TP7-LA 


1.8 


0.72 


0.71 


3.76 




Orlando International Airport; D22-FL 




1.43 


1.54 


2.31 




Site 33, Pile 3, Reinforced Concrete 




0.47 


0.48 


0.67 




Site 33, Pile 4, Reinforced Concrete 




1.31 


1.18 


1.47 




Ft Myers-FL 




1.12 


1.27 


1.24 














1.23 


Apalachicola River Bridge - Pier 3-FL 




0.76 


0.94 


1.83 














0.86 


Apalachicola Bay Bridge - Bent 22-FL 


1.55 


0.94 


0.81 


2.3 














1.21 


Apalachicola Bay Bridge - Bent 16-FL 




0.56 


0.71 




0.98 


Port Orange - Bent 19-FL 




0.87 


1.29 


1.01 














0.28 


Choctahatchee Bay, FL3 




0.83 


1.19 


2.79 














0.83 


Choctahatchee Bay, FL26 


2.28 


1.91 


2.41 


6.24 














1.69 


065-90-0024_and_855-04-0046_Tpl-LA 


0.68 


0.66 


0.61 




0.69 


065-90-0024_and_855-04-0046_Tp2-LA 


0.45 


0.48 


0.39 




0.52 


065-90-0024_and_855-04-0046_TP3-LA 


0.92 


0.81 


0.72 




0.86 


065-90-0024_and_855-04-0046_TP4-LA 


1.02 


0.82 


0.66 




0.94 


260-05-0020_Tickfaw_River_; TPl -LA 


1.09 


1.17 


0.94 




1.22 



271 



Table D-3a (cont.) 



262-06-09_Tickfaw_River_ #1; TPl-LA 




0.24 


0.42 




0.55 


262-06-09_Tickfaw_River_ #1; TP2-LA 




0.21 


0.35 




0.36 


283-09-52_New_Orleans-LA 




0.82 


0.77 




1.26 


424-05-0078_Bayou_Boeuf_Main_; TP2-LA 




0.74 


0.69 




1.02 


424-05-0078_Bayou_Boeuf_Main_; TP5-LA 


1.06 


1.42 


1.11 




2 


424-05-008 l_Bayou_Boeuf_West_; TP2-LA 




0.49 


0.42 




0.59 


424-05-008 l_Bayou_Boeuf_West_; TP3-LA 




0.82 


0.72 




1.26 


424-05-008 l_Bayou_Boeuf_West_; TP4-LA 


0.54 


0.71 


0.52 




0.65 


424-05-0087_Bayou_Ramos_ TPl-LA 




0.75 


0.7 




0.73 


424-05-0087_Bayou_Ramos_ TP2-LA 




0.47 


0.68 




0.87 


424-05-0087_Bayou_Ramos_ TP3-LA 




0.43 


0.55 




0.77 


424-05-0087_Bayou_Ramos_ TP4-LA 




0.57 


0.86 




0.76 


424-05-0087_Bayou_Ramos_ TP5-LA 




0.49 


0.47 




0.65 


424-05-0087_Bayou_Ramos_ TP7-LA 


1.28 


0.68 


0.58 




0.79 


424-06-0005_Bayou_Boeuf_East_F3-LA 


0.5 


0.76 


0.57 




0.95 


424-06-0005_Bayou_Boeuf_East_F4-LA 


0.53 


0.72 


0.51 




0.96 


424-07-0009_Gibson_Raceland_ TPl-LA 




0.88 


0.77 




0.72 


424-07-0009_Gibson_Raceland_TP4-LA 




0.61 


0.56 




0.88 


450-366-02_Luling_Bridge-LA 




0.47 


0.48 




0.65 




0.57 


0.76 


0.58 




1.18 


N 

Average 
Standard deviation 
COV 


34 




85 


74 


32 


1.00 


0.88 


0.93 


1.97 


0.90 


0.52 


0.47 


0.55 


1.21 


0.35 


0.52 


0.54 


0.59 


0.61 


0.39 




3=2.33 


0.35 


0.30 


0.28 


0.57 


0.42 


p=3.0 


0.25 


0.21 


0.19 


0.38 


0.31 



Table D-3b Calibration Resistance Factor for Driven Pile in Mixed Soil 
Using Florida Data Only 



LOCATION 


Davisson 

a Tomlinson 
Nordlund 
Thurman 


Davisson 

fjr-API revised 
Nordlund 
Thurman 


Davisson 
^-Thurman 


Davisson 

Schmertmann 
SPT 


13 

Davisson 

13 

Schmertmann 
CPT 


APP. BAY BRIDGE BENT 101 


0.97 


1.11 


1.03 


3.58 




APP. BAY BRIDGE BENT 133 


1.12 


0.72 


0.62 


2.07 




1-275 34th ST. PINELLAS-FL 


0.5 


0.55 


0.71 


0.88 




DeSOTA CONDOMINIUM MS.-FL 




1.17 


1.22 


1.16 




WASHINGTON CONDOMINIUM 




0.39 


0.46 


0.49 




SUNSHINE SKYWAY SITE 1 A-FL 








1.05 




SUNSHINE SKYWAY SITE 1 B-FL 








0.99 




SUNSHINE SKYWAY SITE 3-FL 








1.51 




SUNSHINE SKYWAY SITE 10-FL 


1.17 


0.95 


0.81 


1.88 




SUNSHINE SKYWAY SITE 13 A-FL 








2.35 




FLORENCE/MARION 3 ASD 




1.56 


1.88 


1.71 




FLORENCE / MARION 3 BSD 


0.46 


0.63 


0.6 


1.2 




FLORENCE / MARION 3 CSD 


0.45 


0.64 


0.66 


1 





272 



Table D-3b (cont.) 



NORTHEAST VILLA MIRADA - 6-FL 




1.22 


1.24 


1.71 




SEAWAY HOTELS, SAND KEY-FL 








2.68 




HOWARD FRANKLAND / LS3-FL 


0.53 


0.99 


0.85 


2.23 




CHOCTAWHATCHEE P-5-FL 




0.85 


0.99 


2.76 




CHOCTAWHATCHEE P-1 1-FL 




1.01 


1.4 


2.49 




CHOCTAWHATCHEE P-17-FL 




1.08 


1.42 


3.13 




CHOCTAWHATCHEE P-23-FL 




0.43 


0.63 


0.91 




CHOCTAWHATCHEE P-29-FL 




0.58 


0.86 


1.38 




CHOCTAWHATCHEE P-35-FL 




0.92 


1.43 


2.17 




HOWARD FRANK. / LS4 SHORT 




3.33 


3.87 


5.21 




CHOCTAWHATCHEE P-41-FL 


1.35 


1.32 


1.34 


3.52 




CHOCTAWHATCHEE FSB-26-FL 




0.38 


0.55 


1.1 




CAPE CANAVERAL T-7-FL 




0.62 


0.67 


0.96 




CAPE CANAVERAL T-14-FL 




0.9 


1.07 


1.34 




HOWARD FRANK. / LS4 LONG-FL? 








0.5 




ACOSTA BRIDGE PEIR F6-FL 




0.88 


1.01 


1.49 




ACOSTA BRIDGE PEIR G13_FL 








1.83 




BUCKMAN BRIDGE TS-13-FL 




0.42 


0.47 


1.19 




BUCKMAN BRIDGE TS-24-FL 


0.51 


0.52 


0.8 


1.07 




BUCKMAN BRIDGE TS-29-FL 




0.47 


0.61 


1.16 




APPALACHICOLA RIVER PIER14-FL 




0.76 


1.01 


1.89 




ArrALACHlCULA KlVbK FlbKzj-rL 




1.15 


i.44 


z.ol 




MAKIJNA BAY CLUB lr/-rL 








1 o c 
l.OJ 




A r>r> AT A /^TJT/^/^T A "D A \/ "D'CXTT' A 1 "CT 

ArrALACHlCULA BAY BbJN 1 41-rL 






i.65 


3.99 




FL 








1.52 




GEORGIA/FLORIDA BOUND ARY-FL 








0.76 




JACKSONVILLE SITE B-FL 








1.83 




JACKSONVILLE SITE D-FL 








1.4 




SAINT JOHN RIVER SITE F-FL 








1.09 




LONGBOAT KEY - SARASOTA-FL 


0.51 


0.75 


0.7 


0.88 




SUNSHINE SKYWAY SITE 13 B-FL 








1.37 




1 19 GRL Piles- White City Bridge, FL 




1.32 


1.39 


2.51 




1 19 GRL Piles- White City Bridge, FL 




1.26 


1.53 


2.32 




Orlando International Airport; D22-FL 




1.43 


1.54 


2.31 




Site 33, Pile 3, Reinforced Concrete 




0.47 


0.48 


0.67 




Site 33, Pile 4, Reinforced Concrete 




1.31 


1.18 


1.47 




Ft Myers-FL 




1.12 


1.27 


1.24 




Apalachicola River Bridge - Pier 3-FL 




0.76 


0.94 


1.83 




Apalachicola Bay Bridge - Bent 22-FL 


1.55 


0.94 


0.81 


2.3 




Apalachicola Bay Bridge - Bent 16-FL 




0.56 


0.71 




0.98 


Port Orange - Bent 19-FL 




0.87 


1.29 


1.01 




Choctahatchee Bay, FL3 




0.83 


1.19 


2.79 




Choctahatchee Bay, FL26 


2.28 


1.91 


2.41 


6.24 














1.69 


N 

Average 


12 


42 


42 


55 


7 


0.95 


0.97 


1.11 


1.87 


1.01 



273 



Table D-3b (cont.) 



Standard deviation 
COV 


0.57 


0.52 


0.61 


1.10 


0.44 


0.60 


0.54 


0.54 


0.59 


0.43 


0) 


|3=2.33 


0.28 


0.33 


0.37 


0.56 


0.43 


3=3.0 


0.19 


0.23 


0.26 


0.38 


0.32 



Table D-3c Calibration Resistance Factor for Driven Pile in Mixed Soil 
Using Lousiana Data Only 



1 OP AXIOM 


R 

Davissoii 

a Tomlinsoii 
Nordlund 
Thiirman 


R 

Davisson 

cc-API revised 
Nordlund 
Thiirraan 


Davisson 
^-Thurman 


13 

Davisson 

Schmeitmann 
SPT 


11 

Davisson 

11 

Sciimertmann 
CPT 


Luling Bridge; TP2-LA 


1.66 


0.65 


0.65 


2.92 




Luling Bridge; TP3; Circular void-LA 




0.79 


0.81 


6.2 




Luling Bridge; TP4; Circular void-LA 


1.72 


0.66 


0.65 


3.42 




Luling Bridge; TPS -LA 


1.84 


0.71 


0.69 


3.61 




Luling Bridge; TP6-LA 


1.74 


0.71 


0.69 


3.59 




Luling Bridge; TP7-LA 


1.8 


0.72 


0.71 


3.76 




065-90-0024_and_855-04-0046_Tpl-LA 


0.68 


0.66 


0.61 




0.69 


065-90-0024_and_855-04-0046_Tp2-LA 


0.45 


0.48 


0.39 




0.52 


065-90-0024_and_855-04-0046_TP3-LA 


0.92 


0.81 


0.72 




0.86 


065-90-0024_and_855-04-0046_TP4-LA 


1.02 


0.82 


0.66 




0.94 


260-05-0020_Tickfaw_River_; TPl -LA 


1.09 


1.17 


0.94 




1.22 


262-06-09_Tickfaw_River_ #1; TPl -LA 




0.24 


0.42 




0.55 


262-06-09_Tickfaw_River_ #1; TP2-LA 




0.21 


0.35 




0.36 


283-09-52_New_Orleans-LA 




0.82 


0.77 




1.26 


424-05-0078_Bayou_Boeuf_Main_; TP2-LA 




0.74 


0.69 




1.02 


424-05-0078_Bayou_Boeuf_Main_; TP5-LA 


1.06 


1.42 


1.11 




2 


424-05-008 l_Bayou_Boeuf_West_; TP2-LA 




0.49 


0.42 




0.59 


424-05-008 l_Bayou_Boeuf_West_; TP3-LA 




0.82 


0.72 




1.26 


424-05-008 l_Bayou_Boeuf_West_; TP4-LA 


0.54 


0.71 


0.52 




0.65 


424-05-0087_Bayou_Ramos_ TPl-LA 




0.75 


0.7 




0.73 


424-05-0087_Bayou_Ramos_ TP2-LA 




0.47 


0.68 




0.87 


424-05-0087_Bayou_Ramos_ TP3-LA 




0.43 


0.55 




0.77 


424-05-0087_Bayou_Ramos_ TP4-LA 




0.57 


0.86 




0.76 


424-05-0087_Bayou_Ramos_ TP5-LA 




0.49 


0.47 




0.65 


424-05-0087_Bayou_Ramos_ TP7-LA 


1.28 


0.68 


0.58 




0.79 


424-06-0005_Bayou_Boeuf_East_F3-LA 


0.5 


0.76 


0.57 




0.95 


424-06-0005_Bayou_Boeuf_East_F4-LA 


0.53 


0.72 


0.51 




0.96 


424-07-0009_Gibson_Raceland_ TPl-LA 




0.88 


0.77 




0.72 


424-07-0009_Gibson_Raceland_TP4-LA 




0.61 


0.56 




0.88 


450-366-02_Luling_Bridge-LA 




0.47 


0.48 




0.65 


855-14-13_Houma-LA 


0.57 


0.76 


0.58 




1.18 


N 

Average 
Standard deviation 
COV 


16 


31 


31 


6 


25 


1.09 


0.68 


0.64 


3.92 


0.87 


0.52 


0.23 


0.16 


1.16 


0.33 


0.48 


0.34 


0.26 


0.30 


0.38 




p=2.33 


0.42 


0.35 


0.39 


2.23 


0.41 


|3=3.0 


0.30 


0.27 


0.31 


1.75 


0.31 



274 



APPENDIX E 

Nominal and Measure Capacity of Driven Pile from Vietnam 



Table E-1 Summary driven pile data from North, Central and south of Vietnam 















Pile 








Soil 




Dimention 


Length 


No 


Name of Project 


Location 


type 


Name 


(mm) 


(m) 


NP-Cl 


32 Hang Trong-Hanoi 


Hanoi 


Clay 


No77 


20x20 


12 


NP-C2 


- 


North Plain 




No22 


20x20 


12 


NP-C3 


6 1 Lac Trung-Hanoi 


Hanoi 


Clay 


No41-A 


25x25 


22 


NP-C4 


- 


North Plain 




No50-B 


25x25 


36 


NP-C5 


- 


- 




N0I8I-B 


25x25 


32 


NP-C6 


- 


- 




No311-B 


25x25 


22 


NP-C7 


- 


- 




No416-B 


25x25 


22 


NP-C8 


Sai Dong-Gia Lam-Hanoi 


Hanoi 


Clay 


F-13 


25x25 


21.8 


NP-C9 


- 


North Plain 




B-13 


25x25 


22.5 


NP-CIO 


- 


- 




B-9 


25x25 


22 


NP-Cll 


- 


- 




E-5 


25x25 


22.1 


NP-C12 


- 


- 




B-1 


25x25 


21.5 


NP-Cl 3 


- 


- 




E-1 


25x25 


21.8 


NP-C14 


NguPhuc-Kim Thanh 


Hai Duong 


Clay 


No2 


25x25 


16 


NP-Cl 5 


Hai Duong 


North Plain 




No3 


25x25 


16 


NP-Cl 6 


- 


- 




No4 


25x25 


16 


NP-Cl 7 


Truong Hoc-Nam Sach 


Hai Duong 


Clay 


TNOl 


20x20 


11 


NP-Cl 8 


Hai Duong 


North Plain 




TN02 


20x20 


11 


NP-C19 


Nha Lam Vice -Nam Sach 


Hai Duong 


Clay 


TNOl 


25x25 


12 


NP-C20 


Hai Duong 


North Plain 




TN02 


25x25 


12 


NP-C21 


Duong 395 -Hai Duong 


Hai Duong 


Clay 


TNl-VH 


30x30 


23 


NP-C22 




North Plain 




TNI -SAT 


30x30 


23 


NP-C23 


16 Cat Bi-HaiPhong 


HaiPhong 


Clay 


Nol 


30x30 


30.2 


NM-C24 


Nhacong vu Cong An-Lao Cai 


Lao Cai 


Clay 


TNl-011 


25x25 


10 


NM-C25 


- 


North 




TN2-051 


25x25 


10.8 


NM-C26 


- 


Mountain 




TN3-114 


25x25 


13.6 


NM-C27 


- 


- 




TN4-172 


25x25 


12 


NM-C28 


Viet Tri-VinhPhu 


VinhPhu 


Clay 


TN02 


30x30 


19.6 


NM-C29 




North 




TN03 


30x30 


17.5 


NM-C30 




Mountain 




TN04 


30x30 


18 


NM-C31 




- 




TN05 


30x30 


18.5 


NM-C32 




- 




TN03B 


30x30 


19 


NM-C33 


Yung Dang-QuangNinh 


QuangNinh 


Clay 


NOl 


25x25 


11.5 


NM-C34 




North 




N02 


25x25 


6.5 


NM-C35 




Mountain 




N03 


25x25 


6.2 


NM-C36 








N04 


25x25 


9.36 


NM-C37 








N02 


25x25 


10 


NM-C38 








N03 


25x25 


10 


NP-C39 


Thinh Long-Nam Dinh 


Nam Dinh 


Clay 


M1PD4 


D=45 


37.2 


NP-C40 




North Plain 




I21PD4 


D=45 


37.2 


NP-C41 








I1PD3 


D=45 


37.2 


NP-C42 








B40PD4 


D=45 


37.2 


NP-C43 








B13PD3 


D=45 


37.2 



275 



Table E-1 (cont.) 



NP-C44 




- 




C23-PD1 


40x40 


39.2 


NP-C45 




- 




K2-PD2 


40x40 


39.1 


NP-C46 




- 




C42-Tuonggoc 


40x40 


31 


Nr-C47 








Ul-rD5 


40x40 


31 


NP-C48 








D38-150 


40x40 


37 


NP-C49 








B38-30 


40x40 


37.1 


NP-Sl 


134 QuanThanh-Hanoi 


Hanoi 


Sand 


TNI 


20x20 


15 


NP-S2 


- 


North Plain 




TN2 


20x20 


22.3 


NP-S3 


- 


- 




TN3 


20x20 


22.6 


NP-S4 


Nha may panasonic-Hanoi 


Hanoi 


Sand 


TNI 


30x30 


25 


NP-S5 


- 


North Plain 




TN2 


30x30 


25 


NP-S6 


- 


- 




TN3 


30x30 


25 


NP-S7 


- 


- 




TN4 


30x30 


25 


NP-S8 


- 


- 




TN5 


30x30 


25 


NP-S9 


- 


- 




TN6 


30x30 


25 


NP-SIO 


- 


- 




TN7 


30x30 


25 


NP-Sll 


- 


- 




TN8 


30x30 


25 


NP-S12 


- 


- 




TN9 


30x30 


25 


NP-Sl 3 


- 


- 




TNIO 


30x30 


25 


NP-S14 


- 


- 




TNll 


30x30 


25 


NP-Sl 5 


- 


- 




TN12 


30x30 


25 


NP-Sl 6 








TN13 


30x30 


25 


NP-Sl 7 


_ 


_ 




TN14 


30x30 


25 


NP-Sl 8 


_ 


_ 




TN15 


30x30 


25 


NP-Sl 9 


- 


- 




TN16 


30x30 


25 










Nol33- 






NP-S20 


CT20A-Viet Hung-Hanoi 


Hanoi 


Sand 


CT20A1 


25x25 


25 


NP-S21 


- 


North Plain 




No37-CT20A2 
Nol33- 


25x25 


25 


NP-S22 








CT20A4 


25x25 


25 


NP-S23 


- 


- 




No66-CT20A 


25x25 


25 


NP-S24 








No37-CT20A1 
Nol33- 


25x25 


25 


NP-S25 


- 


- 




CT20A1 


25x25 


25 


NP-S26 








No37-CT20A2 
Nol33- 


25x25 


25 


NP-S27 








CT20A2 


25x25 


25 


NP-S28 


_ 


_ 




No37-CT20A3 
Nol33- 


25x25 


25 


NP-S29 


- 


- 




CT20A3 


25x25 


25 


NP-S30 


- 


- 




No37-CT20A4 
Nol33- 


25x25 


25 


NP-S31 


- 


- 




CT20A4 


25x25 


25 


NP-S32 


CT20B-Viet Hung-Hanoi 


Hanoi 


Sand 


NOl 


40x40 


36 


NP-S33 




North Plain 




N91 


40x40 


36 


NP-S34 








N164 


40x40 


36 


NP-S35 


Yen Thuong-Gia Lam-Hanoi 


Hanoi 


Sand 


No 122 


25x25 


12 


NP-S36 




North Plain 




No239 


25x25 


12 


NP-S37 








No56 


25x25 


12 


NP-S38 








Noll2 


25x25 


12 



276 



Table E-1 (cont.) 



NP-S39 




- 




N0I6I 


25x25 


12 


NP-S40 


Lai Vu-Hai Duong 


Hai Duong 


Sand 


No77 


25x25 


13 


NP-S41 


Thanh Dong-Hai Duong 


Hai Duong 


Sand 


No30 


25x25 


32.5 


NP-S42 




North Plain 




No78 


25x25 


32.6 


NP-S43 




- 




N08O 


25x25 


33.3 


NP-S44 


Tran Phu-Hai Duong 


Hai Duong 


Sand 


TN-24 


25x25 


29 


NP-S45 




North Plain 




TN-70 


25x25 


29 


NP-S46 




- 




TN-134 


25x25 


29 


NP-S47 


Truong congnhankythuat 


Hung Yen 


Sand 


C2-N0I6 


30x30 


32.5 


NP-S48 


Hung Yen 


North Plain 




D7-No65 


30x30 


33 


NP-S49 




- 




CIO-N0IO2 


30x30 


31.5 


NP-S50 




- 




DI4-N0I4O 


30x30 


32.4 


NP-S51 


Tru so lam viec so thuongmai 


Hai Duong 


Sand 


N037 


25x25 


11.9 


NP-S52 


Hai Duong 


North Plain 




N090 


25x25 


11.4 


NP-S53 




- 




N0208 


25x25 


12.1 


NP-S54 




- 




N0282 


25x25 


14.2 


NP-Ml 


My Dinh-TuLiem-hanoi 


Hanoi 


Mixed 


N01-C144 


35x35 


23.8 


NP-M2 




North Plain 




N02-C65 


35x35 


22.4 


NP-M3 


8 1 Tran Hung Dao-Hanoi 


Hanoi 


Mixed 


No248 


35x35 


21.4 


NP-M4 


- 


North Plain 




No 129 


35x35 


21.8 


NP-M5 


- 


- 




No53 


35x35 


21.8 


NP-M6 


299 Duong CauGiay-Hanoi 


Hanoi 


Mixed 


No64 


35x35 


25 


NP-M7 


- 


North Plain 




No 185 


35x35 


26.6 


NP-M8 


- 


- 




Nol32 


35x35 


26.8 


NP-M9 


- 


- 




No52 


35x35 


25.2 


NP-MIO 


335 Duong CauGiay-Hanoi 


Hanoi 


Mixed 


TN05-108 


35x35 


- 


NP-Mll 


Bo KeHoachDauTu-Hanoi 


Hanoi 


Mixed 


N3-51 


30x30 


35+2 


NP-Ml 2 


- 


North Plain 




N9-92 


30x30 


35+2 


NP-Ml 3 


- 


- 




N8-139 


30x30 


35+2 


NP-M14 


- 


- 




N2-233 


30x30 


35+2 


NP-Ml 5 


- 


- 




N4-558 


30x30 


35+2 


NP-Ml 6 


- 


- 




N7-682 


30x30 


35+2 


NP-Ml 7 


- 


- 




N5-874 


30x30 


35+2 


NP-Ml 8 


Me Tri-TuLiem-Hanoi 


Hanoi 


Mixed 


NT06 


25x25 


27 


NP-Ml 9 


- 


North Plain 




NT05 


25x25 


27 


NP-M20 


- 


- 




NT04 


25x25 


27 


NP-M21 


- 


- 




NT03 


25x25 


27 


NP-M22 


- 


- 




NT02 


25x25 


27 


NP-M23 


- 


- 




NTOl 


25x25 


27 


NP-M24 


DH KienTruc Hanoi 


Hanoi 




NOl-lOF 


20x20 


12 


NP-M25 


- 


North Plain 




N02-7E 


20x20 


12 


NP-M26 


CCl-Dich Vong-CauGiay-Hanoi 


Hanoi 


Mixed 


NTl 


35x35 


25.4 


NP-M27 




North Plain 




NT2 


35x35 


20.4 


NP-M28 








NT3 


35x35 


19 


NP-M29 








N-4 


35x35 


20 


NP-M30 








N-5 


35x35 


20 


NP-M31 


Nha may dong tau Song Hong 


Hanoi 


Mixed 


Al-5 


35x35 


25 


NP-M32 


Hanoi 


North Plain 




Bl-2 


35x35 


25 


NP-M33 








A5-2 


35x35 


25 



277 



Table E-1 (cont.) 



NP-M34 


- 


- 




AlO-5 


35x35 


25 


NP-M35 


- 


- 




B5-2 


35x35 


25 


NP-M36 


- 


- 




BlO-2 


35x35 


25 


NP-M37 


- 


- 




Al 


35x35 


21.4 


NP-M38 


- 


- 




A29 


35x35 


19 


NP-M39 


- 


- 




A60 


35x35 


25.5 


NP-M40 


- 


- 




A55 


35x35 


19.5 


NP-M41 


CT14K-Viet Hung-Hanoi 


Hanoi 


Mixed 


No62 


40x40 


36.4 


NP-M42 


- 


North Plain 




No55 


40x40 


33.5 


NP-M43 


- 


- 




No 172 


40x40 


35.6 


NP-M44 


- 


- 




No336 


40x40 


32.9 


NP-M45 


- 


- 




No243 


40x40 


33.8 


NP-M46 


Van Mo-HaDong-Hanoi 


Hanoi 


Mixed 


SHC220-D8 


25x25 


11.6 


NP-M47 


- 


North Plain 




SHC480-C11 


25x25 


12.4 


NP-M48 


- 


- 




SHC540-C15 


25x25 


11.75 


NP-M49 


- 


- 




SHC103-B13 


25x25 


12 


NP-M50 


- 


- 




SHC28-E4 


25x25 


11.5 


NP-M51 


- 


- 




SHC355-B2 


25x25 


11.3 


NP-M52 


~ 


- 




SHC410-C6 


25x25 


11.5 


NP-M53 


27 Hang Bai - Hanoi 


Hanoi 


Mixed 


NTl-HB 


25x25 


21,8 


NP-M54 


192B QuanThanh - Hanoi 


Hanoi 


Mixed 


5QT 


30x30 


21,5 


NP-M55 


- 


North Plain 




7QT 


30x30 


21 


NP-M56 


DHXD- Hanoi 


Hanoi 


Mixed 


NT06 


35x35 


19 


NP-M57 


- 


North Plain 




NT 10 


35x35 


13 


NP-M58 


VinhPhuc-Hanoi 


Hanoi 


Mixed 


TNI 


25x25 


15 


NP-M59 




North Plain 




TN2 


25x25 


15 


NP-M60 




- 




TN2 


25x25 


15 


NP-M61 


Sieuthi 7 tang- Hai Duong 


Hai Duong 


Mixed 


TNOl-103 


30x30 


38.4 


NP-M62 




North Plain 




TN2-60 


30x30 


38.1 


NP-M63 


Cau Lac boHuu Tri Nguyen Trai 


Hai Duong 


Mixed 


Dl-Cx7 


20x20 


10.8 


NP-M64 


Hai Duong 


North Plain 




D5-Fxl2 


20x20 


10.9 


NP-M65 




- 




D2-Ex5 


20x20 


11 


NP-M66 


I): 11 Vien Thong Thanh Ha 


Hai Duong 


Mixed 


Nol 


25x25 


17 


NP-M67 


Hai Duong 


North Plain 




No2 


25x25 


17 


NP-M68 


KyThucXa-Truong Cao Dang 


Hai Duong 


Mixed 


TNl-129 


25x25 


39 


NP-M69 


Hai Duong 


North Plain 




TN2-95 


25x25 


39 


NP-M70 


- 


- 




TN3-32 


25x25 


39 


NP-M71 


Lai Cach-Cam Giang-Hai Duong 


Hai Duong 


Mixed 


TN57 


25x25 


35 


NP-M72 




North Plain 




TN355 


25x25 


40 


NP-M73 




- 




TN312 


25x25 


24.5 


NP-M74 




- 




TN121 


25x25 


23 


NP-M75 


Great Wall Plaza-ThanhNien St 


Hai Duong 


Mixed 


No50 


35x35 


40 


NP-M76 


Hai Duong 


North Plain 




No206 


35x35 


40 


NP-M77 










35x35 


40 


NM-M78 


Khu Du Lich NhaNghi-Chi Linh 


Hai Duong 


Mixed 


No49 


D=30 


21.5 


NM-M79 


Hai Duong 


North Plain 






D=30 


21.5 


NM-M80 










D=30 


21.5 


NP-M81 


Nha Tap Luyen Da Nang 


Hai Duong 


Mixed 


TNOl 


25x25 


30.9 


NP-M82 


Hai Duong 


North Plain 




TN02 


25x25 


30.9 



278 



Table E-1 (cont.) 



NP-M83 


Tru So Lam Viec - Van An 


Hai Duong 


Mixed 


TNOl 


20x20 


8.2 


NP-M84 


Hai Duong 


North Plain 




TN02 


20x20 


8.2 


NP-M85 


BenhVienLaoPhoi 


Hai Duong 


Mixed 


TNOl 


25x25 


30 


NP-M86 


Hai Duong 


North Plain 




TN02 


25x25 


30 


NP-M87 


Nha Lam Viec Cong An-GiaLoc 


Hai Duong 


Mixed 


TNOl 


25x25 


18 


NP-M88 


Hai Duong 


North Plain 




TN02 


25x25 


18 


NP-M89 


Cam Phuc-Cam Giang 


Hai Duong 


Mixed 


TN04 


20x20 


13.25 


NP-M90 


Hai Duong 


North Plain 




TN40 


20x20 


13.25 


NP-M91 


ngan hang congthuong 


Hai Duong 


Mixed 


TN14 


30x30 


32.5 


NP-M92 


Hai Duong 


North Plain 




TN57 


30x30 


32.6 


NP-M93 




- 




TN80 


30x30 


33.5 


NP-M94 


Ngan Hang BacHai Duong 


Hai Duong 


Mixed 


TN-1 


25x25 


10 


NP-M95 


- 


North Plain 




TN-175 


25x25 


10 


NP-M96 


- 


- 




TN-1 86 


25x25 


10.2 


NP-M97 


Bo Chi HuyQuan Su Hai Duong 


Hai Duong 


Mixed 


N44 


25x25 


12 


NP-M98 


- 


North Plain 




N108 


25x25 


12 


NP-M99 


Trung Tam Thuong Mai Van Hoa 


HaiPhong 


Mixed 


COl 


40x40 


38 


NP-MIOO 


HaiPhong 


North Plain 




C02 


40x40 


38 


NP-MlOl 




- 




C03 


40x40 


38 


NP-M102 




- 




C04 


40x40 


38 


NP-M103 


TrungTrac-Van Lam-Hung Yen 


Hung Yen 


Mixed 


TN31-C10 


20x20 


18 


NP-M104 




North Plain 




TN137-A24 


20x20 


18 


NP-M105 




- 




TN94-C31 


20x20 


18 


NP-M106 


So Tai Nguyen Moi Truong 


Thai Binh 


Mixed 


NT 1TB 


35x35 


4 


NP-M107 


Thai Binh 


North Plain 




TN02TB 


35x35 


4 


NP-M108 


- 


- 




TN03TB 


35x35 


4 


CP-Cl 


Dong Hoi-QuangBinh 


Quang 


Clay 


N0I62-A6 


25x25 


11 


CP-C2 




Binh 




No242-F9 


25x25 


12 


CP-C3 




Central 




No284-A10 


25x25 


11 


CP-C4 




Plain 




No41-F3 


25x25 


10.4 


CP-C5 




- 




No4-Al 


25x25 


11.4 


CP-C6 


Phan Chu Trinh-Da Lat-Lam Dong 


Da Lat 


Clay 


No550 


30x30 


18 


CP-C7 




Central 




No530 


30x30 


18 


CP-C8 




Mountain 




No228 


30x30 


18 


CP-C9 




- 




No31 


30x30 


18 


CP-CIO 




- 




Nol38 


30x30 


18 


CP-Cll 


Tuongdai Le Loi-ThanhHoa 


ThanhHoa 


Clay 


Nol 


30x30 


16 


CP-SI 


Nha may dong tau Danang 


Da Nang 


Sand 


TDl 


40x40 


34.1 






Central 










CP-S2 


- 


Plain 




TD2 


40x40 


31.8 


CP-S3 


- 






TD3 


40x40 


33.6 


CP-S4 


- 






TD4 


40x40 


31.5 


CP-S5 








TD5 


40x40 


30.6 


CP-MI 


Doosan 


QuangNgai 


Mixed 


A-3-6 (TPl) 


D=40 


20.3 






Central 










CP-M2 




Plain 




Y3-A33 (TP2) 


D=40 


25.6 


CP-M3 








RT 25 (TP3) 


D=40 


25.3 


CP-M4 








B-17-2 (TP4) 


D=40 


25.7 


CP-M5 








A20 (TPS) 


D=40 


26.4 



279 



Table E-1 (cont.) 



CP-M6 








Y4-12(TP6) 
Y2-1-D10 


D=40 


22.7 


CP-M7 








(TP7) 


D=40 


24.7 


CP-M8 


_ 


_ 




B-4-06 (TP8) 


D=40 


26 


CP-M9 


- 


- 




A-5-03 (TP9) 
MF2.30 


D=40 


25.6 


CP-MIO 


- 


- 




(TP 10) 


D=40 


26.4 


CP-Mil 








A-3-2 fTPl 1^ 


D=40 


28 


CP-MI 2 








ST05 (TV\2) 
Y6-B14 


D=40 


28.4 


CP-MI 3 








(TP 13) 


D=40 


24.7 


CP-M14 








Y5-12 (TP14) 
Y7-B12 


D=40 


24.3 


CP-MI 5 








(TP 15) 
MF.Y1-J30 


D=40 


26.5 


CP-MI 6 


- 


- 




(TP 16) 


D=40 


30.05 


CP-MI 7 


- 


- 




A-2-1 (TP 17) 


D=40 


16.8 


CP-MI 8 


- 


- 




B-22 


D=40 


27.1 


CP-MI 9 


- 


- 




A-29 


D=40 


27.1 


CP-M20 


San bay -NhaGaHanhKhach 


Da Nang 
Central 


Mixed 


N03(Pl-480) 


40x40 


20.5 


CP-M21 


Danang 


Plain 




N04(P 1-532) 


40x40 


23.85 


CP-M22 


- 


- 




N06(P2-57) 


40x40 


20.7 


CP-M23 


- 


- 




N07(P2-63) 


40x40 


20.92 


CP-M24 


- 


- 




N09(P3-159) 


40x40 


20.78 


CP-M25 


- 


- 




N10(Pl-347) 


40x40 


22.32 


CP-M26 


- 


- 




N1(P1-151) 


40x40 


24.95 


CP-M27 








N2(P 1-221) 


40x40 


26.25 


CP-M28 




: 




N5(P2-3) 


40x40 


23.89 


CP-M29 


- 


- 




N8(P3-7) 


40x40 


24.15 


CP-M30 


- 


- 




N11(P3-411) 


40x40 


26.36 


CP-M3 1 


- 


- 




N12(P3-510) 


40x40 


25.1 


CP-M32 


- 


- 




N13(P5-8) 


30x30 


22.8 


CP-M33 


- 


- 




N14(P4-30) 


30x30 


26.1 


CP-M34 


PhongPhu-TP Hue 


Hue 
Central 


Mixed 


DlO-26 


30x30 


19 


CP-M35 




Plain 




D5-458 


30x30 


20 


CP-M36 




- 




T13-309 


30x30 


12 


CP-M37 




- 




T12-290 


30x30 


12 


CP-M38 




- 




C6-405 


30x30 


16 


CP-M39 








C8-144 


30x30 


16 


CP-M40 


TP Vinh- Nghe An 


Nghe An 
Central 


Mixed 


N02 


25x25 


24 


CP-M41 




Plain 




N03 


25x25 


24 


CP-M42 








NOl-122 


25x25 


24 


CP-M43 








N02-23 


25x25 


24 


CP-M44 


Dung Quat 


QuangNgai 
Central 


Mixed 


l-A-1-8 


D=40 


23 


CP-M45 




Plain 




1-B-l-l 


D=40 


23.1 


CP-M46 








l-A-8-3 


D=40 


23.5 


CP-M47 








l-B-12-1 


D=40 


23.1 



280 



Table E-1 (cont.) 



CP-M48 


- 


- 




l-B-7-3 


D=40 


23 


CP-M49 


- 


- 




l-F-4-3 


D=40 


23.2 


CP-M50 


- 


- 




l-J-4-4 


D=40 


23 


CP-M5 1 


- 


- 




l-J-2-4 


D=40 


23.3 


CP-M52 


- 


- 




C-3-4 


D=40 


24 


CP-M53 


- 


- 




TP-A-17-3 


D=40 


24 


SP-Cl 


CauPhu My- Saigon 


SaiGon 


Clay 


No22 


40x40 


27.7 


SP-C2 


Cong tyximangHiepPhuoc-Saigon 


SaiGon 


Clay 


No22 


30x30 


36 


SP-Ml 


Tong KhoXangDauNha Be-Saigon 


SaiGon 


Mixed 


NO 1 -A3 3 


30x30 


41.8 


SP-M2 




South Plain 




N02-A33 


30x30 


44.5 


SP-M3 




- 




N03-A33 


30x30 


45 


SP-M4 




- 




N04-A32 


30x30 


39 


SP-M5 




- 




N05-A32 


30x30 


39 


SP-M6 




- 




N06-A32 


30x30 


37 


SP-M7 




- 




N10-A26 


30x30 


34 


SP-M8 




- 




N11-A26 


30x30 


35.5 


SP-M9 




- 




N12-A26 


30x30 


35 




Intel-corp- Nut giao thong Thu 












SP-MIO 


Due 


SaiGon 


Mixed 


TPl 


20x20 


18 


SP-Ml 1 


SaiGon 


South Plain 




TP2 


20x20 


18 


SP-Ml 2 


- 


- 




TP3 


20x20 


18 


SP-Ml 3 


- 


- 




TP4 


20x20 


18 


SP-M14 


- 


- 




TPS 


D=30 


24 


SP-Ml 5 


- 


- 




TP6 


D=30 


24 


SP-Ml 6 


- 


- 




TP7 


D=40 


22 


SP-Ml 7 


UngThanhHao Mon -Phuong 7-Q8 


SaiGon 


Mixed 


NOl-CDl 


40x40 


43.6 


SP-Ml 8 


Saigon 


South Plain 




N02-CD2 


40x40 


43.8 


SP-Ml 9 


ASU-Phu My-Ba Ria-Vung Tau 


Vung Tau 


Mixed 


N01-L129-P2 


30x30 


8.3 


SP-M20 


SaiGon 


South Plain 




N02-L4-P1 


30x30 


8.35 


SP-M21 


- 


- 




N03-L14-P2 


30x30 


12.3 


SP-M22 


- 


- 




N04-L33-P1 


30x30 


9.05 




Nha May Su lyNuoc Thai - 












SP-M23 


SaiGon 


SaiGon 


Mixed 


BLB-TPl 


40x40 


41,77 


SP-M24 


- 


South Plain 


Mixed 


LP-TPl 


40x40 


40,19 


SP-M25 


- 


- 


Mixed 


FB-TP2 


40x40 


39,3 


SP-M26 






Mixed 


WTF-TPl 


40x40 


42,15 


SP-M27 






Mixed 


DDS-TPl 


40x40 


38,86 


SP-M28 






Mixed 


Tl-TPl 


40x40 


38,8 


SP-Sl 


Nha May Su lyNuoc Thai - Sai 




Sand 


WTF-TP3 


40x40 


39,47 


SP-S2 


Gon 




Sand 


WTF-TP4 


40x40 


39,45 


SP-S3 






Sand 


LP-TP2 


40x40 


40,1 


SP-S4 






Sand 


IFB-TPl 


40x40 


39,54 



281 



Table E-2 Summary measure capacity of driven pile from North, Central and South of Vietnam by 

different criterion 





V-^ 111 11 a iViClllUU 


oU /o V^lllll S iViclIlUU 


i-'d.VlSlUll a IlltllluU 


1 " 




7 1 /I 

/LA 


^7 1 


Zo.o 


/lA n 
40. u 




JO.O 


47 1 


jj.O 


44 n 




1 on ^ 
izU.j 


/I 




yo.u 


JNr-C4 


1 An n 


07 n 

/.9 


oz.^ 


90.0 




iZj.U 


1 nn n 

iUU.U 


Q7 n 


1 n 1 n 




1 n 

iZZ.U 


07 A 


OA n 

Vu.U 


1 nn n 




Q/l 7 


A7 Q 


70 n 
/z.u 


7A n 

/D.U 


IMr-v^o 


lAl. Q 


1 1 


IJO.V 


1 40 




ZjU.U 


zUU.U 


1 A^ 7 


1 S9 C 




1 88 7 


1 SO Q 


1^14 


11^0 
i J J .u 


MP PI 1 


917 4 


1 7^ Q 


1 47 n 


1 40 9 


NP-PI 9 


1 79 4 


1 ^7 




1 


>JP PI ^ 


9^9 f, 

Z JZ.U 


1 86 




1 SO 


NP-P 1 4 

IMP V, i T- 


8Q ^ 


71 4 




68 


NP-C15 


79.4 


63.5 


32.0 


50.0 


NP-C16 


78.7 


63.0 


50.0 


62.5 


NP-C 1 7 


30 1 


24. 1 


20.0 


20.0 


"MP PI 8 


9Q 




9 1 n 


9 1 


NP-P1 Q 




94 9 


1 S 


1 7 8 


IMP V^Z.V 




94 S 


1 7 S 


1 7 S 
i / . J 


i\rp P9 1 


L LKj.J 


0^ 


77 


Q4 ^ 


"MP P99 


1 40 ^ 


110 4 


11^0 


1 1 S 


■\TP POl 


1 H/l 1 


OJ.J 




7n n 

/U.U 


is.T\/r PO/i 


1 'J 'J 'J 


1 HA 7 


1 1 9 S 


191 

izi.y 


l\iVi-v^Zj 




1 1 Q /I 


1 1 Q n 


1 90 s 


XT\/f PI A 


1 ^1 c 


1 S'X c 

i JJ.O 


1 SI c 

i JJ.O 


1 S'J 8 
i JJ.O 


l\iVi-v^Z / 




1 9"^ 1 


lion 
i lyM 


1 90 S 

i/y. J 


INM-L'Zo 


1/17 1 


1 1 7 A 


1 1 7 n 
1 1 / .U 


1 o< n 
izj.U 


JNM-Czy 


linn 


yj.Z 




1 OA o 

iOo.O 


NM-C30 


119.0 


95.2 


103.3 


109.0 


NM-n 1 


131.6 


105.3 


115.0 


120.0 


I >l iVl V-- JZ. 


J44 Q 

I '-f-'-t. y 


775 9 


117.0 


126.0 


NM-Cll 


169.5 


135.6 


75.0 


105.0 


NM-r34 


48.8 


39.0 


22.0 


36.0 


NM-CIS 


105.3 


84.2 


60.0 


83.0 


NM-C36 


142.9 


114.3 


66.0 


97.0 


NM-C37 


109.9 


87.9 


68.0 


86.0 


NM-C38 


104.2 


83.3 


68.0 


84.0 


NP-Sl 


54.3 


43.5 


46.0 


49.5 


NP-S2 


52.9 


42.3 


45.0 


47.5 


NP-S3 


59.5 


47.6 


52.5 


54.0 


NP-S4 


131.6 


105.3 


112.5 


116.7 


NP-S5 


135.1 


108.1 


116.1 


119.5 


NP-S6 


125.0 


100.0 


105.9 


110.0 


NP-S7 


140.8 


112.7 


118.0 


122.0 



282 



Table E-2 (cont.) 



NP-S8 


133.3 


106.7 


114.3 


117.6 


NP-S9 


137.0 


109.6 


112.5 


115.5 


NP-SIO 


135.1 


108.1 


115.3 


118.8 


NP-Sll 


128.2 


102.6 


115.3 


118.8 


NP-S12 


119.0 


95.2 


103.2 


107.2 


NP-S13 


131.6 


105.3 


112.5 


116.7 


NP-S14 


126.6 


101.3 


109.7 


113.4 


NP-S15 


135.1 


108.1 


116.5 


119.8 


NP-S16 


126.6 


101.3 


112.5 


114.1 


NP-S17 


129.9 


103.9 


112.5 


115.4 


NP-S18 


131.6 


105.3 


108.8 


113.5 


NP-S19 


125.0 


100.0 


105.4 


109.5 


NP-S20 


101.0 


80.8 


85.3 


88.0 


NP-S21 


133.3 


106.7 


100.0 


102.0 


NP-S22 


147.1 


117.6 


111.8 


112.0 


NP-S23 


85.5 


68.4 


74.0 


76.2 


NP-S24 


97.1 


77.7 


83.1 


85.5 


NP-S25 


129.9 


103.9 


95.0 


98.3 


NP-S26 


136.99 


109.6 


120.0 


120.0 


NP-S27 


105.3 


84.2 


90.4 


92.5 


NP-S28 


117.6 


94.1 


99.3 


100.5 


NP-S29 


102.0 


81.6 


87.0 


89.0 


NP-S30 


126.6 


101.3 


99.7 


101.5 


NP-S31 


96.2 


76.9 


79.8 


83.2 


NP-S32 


500.0 


400.0 


410.0 


356.0 


NP-S33 


416.7 


333.3 


337.4 


305.0 


NP-S34 


312.5 


250.0 


279.0 


270.0 


NP-S35 


81.3 


65.0 


65.0 


68.0 


NP-S36 


85.5 


68.4 


72.0 


75.0 


NP-S37 


73.5 


58.8 


65.0 


67.0 


NP-S38 


76.3 


61.1 


59.0 


60.0 


NP-S39 


84.0 


67.2 


58.0 


60.0 


NP-S40 


60.2 


48.2 


36.5 


48.8 


NP-S41 


48.8 


39.0 


40.1 


45.5 


NP-S42 


46.7 


37.4 


39.6 


44.3 


NP-S43 


46.5 


37.2 


40.0 


43.9 


NP-S44 


60.6 


48.5 


45.0 


52.0 


NP-S45 


60.2 


48.2 


45.0 


52.0 


NP-S46 


103.1 


82.5 


52.5 


69.0 


NP-S47 


277.8 


222.2 


155.0 


155.0 


NP-S48 


208.3 


166.7 


145.0 


145.0 


NP-S49 


163.9 


131.1 


133.0 


133.0 


NP-S50 


161.3 


129.0 


114.0 


114.0 


NP-S51 


83.3 


66.7 


42.0 


60.0 


NP-S52 


57.5 


46.0 


40.0 


50.0 


NP-S53 


76.9 


61.5 


47.5 


61.7 


NP-S54 


80.0 


64.0 


49.0 


62.0 


NP-Ml 


172.4 


137.9 


158.0 


156.0 


NP-M2 


227.3 


181.8 


179.0 


184.0 



283 



Table E-2 (cont.) 



NP-M3 


270.3 


216.2 


110.0 


142.0 


NP-M4 


192.3 


153.8 


137.5 


152.3 


NP-M5 


222.2 


177.8 


137.5 


155.6 


NP-M6 


370.4 


296.3 


255.0 


245.0 


NP-M7 


344.8 


275.9 


275.0 


260.0 


NP-M8 


370.4 


296.3 


285.0 


265.0 


NP-M9 


344.8 


275.9 


239.0 


233.0 


NP-MIO 


186.2 


149.0 


140.0 


140.0 


NP-Ml 1 


175.4 


140.4 


138.0 


145.0 


NP-M12 


175.4 


140.4 


137.0 


145.0 


NP-M13 


178.6 


142.9 


139.0 


147.0 


NP-Ml 4 


175.4 


140.4 


138.0 


145.0 


NP-M15 


175.4 


140.4 


138.0 


145.0 


NP-Ml 6 


172.4 


137.9 


136.0 


144.0 


NP-Ml 7 


158.7 


127.0 


133.0 


139.0 


NP-Ml 8 


147.1 


117.6 


115.0 


111.2 


NP-Ml 9 


137.0 


109.6 


101.5 


103 


NP-M20 


166.7 


133.3 


120.0 


113.0 


NP-M21 


129.9 


103.9 


99.5 


98.5 


NP-M22 


158.7 


127.0 


105.0 


103.0 


NP-M23 


153.8 


123.1 


101.5 


105.5 


NP-M24 


59.5 


47.6 


42.0 


50.0 


NP-M25 


41.3 


33.1 


35.0 


38.3 


NP-M26 


238.1 


190.5 


180.0 


184.5 


NP-M27 


238.1 


190.5 


169.0 


182.0 


NP-M28 


243.9 


195.1 


183.0 


192.5 


NP-M29 


243.9 


195.1 


203.0 


209.0 


NP-M30 


250.0 


200.0 


196.0 


203.5 


NP-M3 1 


204.1 


163.3 


140.6 


152.0 


NP-M32 


212.8 


170.2 


149.2 


158.7 


NP-M33 


181.8 


145.5 


127.0 


138.8 


NP-M34 


227.3 


186.0 


142.0 


155.7 


NP-M35 


166.7 


133.3 


127.5 


136.5 


NP-M36 


131.6 


105.3 


110.6 


117.4 


NP-M41 


476.2 


381.0 


327.6 


375.0 


NP-M42 


434.8 


347.8 


342.0 


310.0 


NP-M43 


454.5 


363.6 


310.0 


278.0 


NP-M44 


312.5 


250.0 


284.0 


276.8 


NP-M45 


322.6 


258.1 


267.0 


256.4 


NP-M46 


107.5 


86.0 


60.0 


80.0 


NP-M47 


74.6 


59.7 


48.0 


61.0 


NP-M48 


149.3 


119.4 


69.0 


97.0 


NP-M49 


84.7 


67.8 


56.0 


70.0 


NP-M50 


120.5 


96.4 


64.0 


87.0 


NP-M51 


69.9 


55.9 


50.0 


60.0 


NP-M52 


65.4 


52.3 


48.0 


57.4 


NP-M53 


77.5 


62.0 


57.0 


66.0 


NP-M54 


185.2 


148.1 


133.4 


141.5 


NP-M55 


178.6 


142.9 


134.0 


141.5 



284 



Table E-2 (cont.) 



NP-M56 


181.8 


145.5 


139.5 


146.5 


NP-M57 


161.3 


129.0 


133.0 


138.0 


NP-M58 


108.6 


86.9 


78.0 


89.0 


NP-M59 


83.1 


66.5 


70.0 


76.0 


NP-M60 


100.4 


80.3 


76.0 


85.0 


NP-M61 


277.8 


222.2 


187.0 


158.0 


NP-M62 


277.8 


222.2 


161.9 


140.0 


NP-M63 


53.8 


43.0 


30.0 


41.7 


NP-M64 


38.5 


30.8 


26.0 


33.0 


NP-M65 


43.7 


34.9 


24.0 


34.4 


NP-M66 


51.8 


41.5 


38.0 


45.0 


NP-M67 


59.9 


47.9 


42.0 


50.0 


NP-M68 


111.1 


88.9 


70.0 


76.0 


NP-M69 


142.9 


114.3 


80.0 


84.0 


NP-M70 


142.9 


114.3 


80.0 


84.0 


NP-M71 


147.1 


117.6 


109.0 


102.0 


NP-M72 


92.6 


74.1 


80.0 


80.0 


NP-M73 


108.7 


87.0 


78.0 


84.0 


NP-M74 


117.6 


94.1 


78.0 


92.0 


NP-M75 


357.1 


285.7 


231.0 


190.5 


NP-M76 


344.8 


275.9 


266.0 


225.0 


NP-M77 


357.1 


285.7 


236.0 


200.0 


NM-M78 


186.6 


149.3 


132.0 


135.0 


NM-M79 










NM-M80 










NP-M81 


96.2 


76.9 


65.0 


75.0 


NP-M82 


109.9 


87.9 


72.0 


82.0 


NP-M83 


68.5 


54.8 


26.0 


43.0 


NP-M84 


78.1 


62.5 


27.0 


49.0 


NP-M85 


78.1 


62.5 


50.0 


58.0 


NP-M86 


90.9 


72.7 


57.0 


64.0 


NP-M87 


104.2 


83.3 


68.0 


80.0 


NP-M88 


117.6 


94.1 


70.0 


85.0 


NP-M89 


33.8 


27.0 


18.0 


26.3 


NP-M90 


36.9 


29.5 


20.0 


28.3 


NP-M91 


111.1 


88.9 


90.0 


93.6 


NP-M92 


112.4 


89.9 


90.0 


93.3 


NP-M93 


111.1 


88.9 


90.0 


93.3 


NP-M94 


126.6 


101.3 


78.0 


99.0 


NP-M95 


114.9 


92.0 


76.0 


93.5 


NP-M96 


116.3 


93.0 


77.0 


94.3 


NP-M97 


106.4 


85.1 


45.0 


61.2 


NP-M98 


79.4 


63.5 


45.0 


61.2 


NP-M99 


217.4 


173.9 


192.0 


192.0 


NP-MIOO 










NP-MlOl 










NP-M102 


172.4 


137.9 


158.0 


158.0 


NP-M103 


74.6 


59.7 


62.5 


65.5 



285 



Table E-2 (cont.) 



NP-M104 


64.9 


51.9 


57.0 


59.0 


NP-M105 


103.6 


82.9 


76.0 


80.0 


NP-M106 


222.2 


177.8 


172.0 


162.0 


NP-M107 


175.4 


140.4 


147.0 


144.0 


NP-M108 


212.8 


170.2 


164.8 


157.0 


CP-Cl 


129.9 


103.9 


90.0 


116.0 


CP-C2 


144.5 


115.6 


100.0 


116.0 


CP-C3 


163.9 


131.1 


122.0 


138.0 


CP-C4 


129.9 


103.9 


95.0 


115.0 


CP-C5 


151.5 


121.2 


120.0 


127.0 


CP-C6 


181.8 


145.5 


126.0 


126.0 


CP-C7 


370.4 


296.3 


213.0 


214.0 


CP-C8 


227.3 


181.8 


168.0 


175.0 


CP-C9 


285.7 


228.6 


213.0 


215.0 


CP-CIO 


312.5 


250.0 


196.0 


202.0 


CP- SI 


152.0 


152.0 


152.0 


152.0 


CP-S2 


231.2 


231.2 


231.2 


231.2 


CP- S3 


144.5 


144.5 


144.5 


144.5 


CP-S4 


249.6 


249.6 


249.6 


249.6 


CP-S5 


157.2 


157.2 


157.2 


157.2 


CP-MI 


217.4 


173.9 


180.0 


190.0 


CP-M2 


250.0 


200.0 


210.0 


210.8 


CP-M3 


312.5 


250.0 


260.0 


254.0 


CP-M4 


227.3 


181.8 


188.0 


191.0 


CP-M5 


434.8 


347.8 


255.0 


257.0 


CP-M6 


238.1 


190.5 


205.0 


208.0 


CP-M7 


357.1 


285.7 


277.0 


227.0 


CP-M8 


217.4 


173.9 


180.0 


187.5 


CP-M9 


303.0 


242.4 


231.0 


227.0 


CP-MIO 


344.8 


275.9 


280.0 


267.0 


CP-Mil 


175.4 


140.4 


162.0 


165.5 


CP-MI 2 


344.8 


275.9 


283.0 


283.0 


CP-MI 3 


277.8 


222.2 


226.0 


226.8 


CP-MI 4 


200.0 


160.0 


168.8 


175.7 


CP-MI 5 


357.1 


285.7 


227.0 


227.0 


CP-MI 6 


333.3 


266.7 


284.0 


268.0 


CP-MI 7 


227.3 


181.8 


187.5 


202.1 


CP-M20 


416.7 


333.3 


260.0 


274.5 


CP-M21 


370.4 


296.3 


269.0 


272.0 


CP-M22 


384.6 


307.7 


260.0 


270.5 


CP-M23 


344.8 


275.9 


260.0 


266.5 


CP-M24 


434.8 


347.8 


255.0 


266.5 


CP-M25 


555.6 


444.4 


304.5 


309.8 


CP-M26 


416.7 


333.3 


260.0 


274.5 


CP-M27 


476.2 


381.0 


273.0 


273.0 


CP-M28 


476.2 


381.0 


273.0 


273.0 


CP-M29 


416.7 


333.3 


260.0 


274.5 


CP-M30 


434.8 


347.8 


250.0 


258.0 


CP-M3 1 


370.4 


296.3 


269.0 


272.0 



286 



Table E-2 (cont.) 



CP-M32 


270.3 


216.2 


224.0 


216.0 


CP-M33 


294.1 


235.3 


172.3 


173.0 


CP-M34 


285.7 


188.0 


160.0 


175.0 


CP-M35 


158.7 


127.0 


154.5 


155.1 


CP-M36 


196.1 


156.9 


125.4 


148.5 


CP-M37 


196.1 


156.9 


125.4 


148.5 


CP-M38 


196.1 


156.9 


122.0 


142.0 


CP-M39 


232.6 


186.0 


113.0 


142.0 


CP-M40 


133.3 


106.7 


94.0 


98.0 


CP-M41 


139.7 


111.7 


94.0 


98.0 


CP-M42 


126.6 


101.3 


100.0 


102.0 


CP-M43 


114.5 


91.6 


86.0 


91.0 


SP-Cl 


363.6 


290.9 


253.0 


253.0 


SP-C2 


100.0 


80.0 


76.0 


79.0 


SP-Ml 


200.0 


160.0 


141.0 


133.0 


SP-M2 


192.3 


153.8 


113.0 


124.2 


SP-M3 


217.4 


173.9 


142.0 


164.5 


SP-M4 


140.8 


112.7 


105.0 


104.0 


SP-M5 


138.9 


111.1 


119.0 


120.0 


SP-M6 


196.1 


156.9 


142.0 


133.0 


SP-M7 


196.1 


156.9 


134.5 


140.0 


SP-M8 


208.3 


166.7 


144.5 


155.0 


SP-M9 


169.5 


135.6 


130.0 


126.3 


SP-MIO 


106.4 


85.1 


82.5 


85.7 


SP-Mll 


113.6 


90.9 


90.0 


91.3 


SP-Ml 2 


116.3 


93.0 


93.0 


95.0 


SP-Ml 3 










SP-Ml 4 


133.3 


106.7 


100.0 


100.0 


SP-Ml 5 










SP-Ml 6 


300.3 


240.2 


245.0 


250.0 


SP-Ml 7 


526.3 


421.1 


445.0 


350.0 


SP-Ml 8 


769.2 


615.4 


618.0 


410.0 


SP-Ml 9 


157.7 


126.2 


132.0 


144.1 


SP-M20 


157.8 


126.3 


128.0 


142.6 


SP-M21 


193.5 


154.8 


150.0 


170.0 


SP-M22 


191.5 


153.2 


110.0 


150.0 


SP-M23 


178.6 


142.9 


151.5 


153.0 


SP-M24 


270.3 


216.2 


194.5 


188.5 


SP-M25 


200.0 


160.0 


162.3 


164.0 


SP-M26 


232.6 


186.0 


189.5 


186.0 


SP-M27 


158.7 


127.0 


141.0 


143.7 


SP-M28 


192.3 


153.8 


156.0 


160.0 


SP-Sl 


232.6 


186.0 


180.5 


181.8 


SP-S2 


227.3 


181.8 


165.5 


167.5 


SP-S3 


158.7 


127.0 


141.0 


143.7 


SP-S4 


192.3 


153.8 


151.0 


153.6 



287 



Table E-3 Summary nominal capacity of driven pile in Cohesionless Soil from North, Central 

and South of Vietnam by different method 





Nordlund 


SPT 


OPeck, Hanson and 
Thornburn 


(J> from 
Schmertmann 


OClllilCl llilcUlll kJ-T 1 




Qi 


Q2 


Q3 


Q4 


NP-Sl 


57.35 


93.23 


51.98 


49.12 


NP-S2 


60.36 


98.14 


54.71 


51.71 


NP-S3 


63.38 


103.05 


57.45 


54.29 


NP-S4 


176.29 


277.69 


137.14 


142.88 


NP-S5 


174.66 


275.12 


135.88 


141.56 


NP-S6 


173.03 


272.55 


134.61 


140.24 


NP-S7 


171.40 


269.98 


133.34 


138.91 


NP-S8 


169.76 


267.41 


132.07 


137.59 


NP-S9 


168.13 


264.84 


130.80 


136.27 


NP-SIO 


166.50 


262.27 


129.53 


134.94 


NP-Sl 1 


164.87 


259.70 


128.26 


133.62 


NP-S12 


163.23 


257.12 


126.99 


132.30 


NP-Sl 3 


161.60 


254.55 


125.72 


130.97 


NP-S14 


159.97 


251.98 


124.45 


129.65 


NP-Sl 5 


158.34 


249.41 


123.18 


128.33 


NP-Sl 6 


156.70 


246.84 


121.91 


127.01 


NP-Sl 7 


155.07 


244.27 


120.64 


125.68 


NP-Sl 8 


153.44 


241.70 


119.37 


124.36 


NP-Sl 9 


151.81 


239.13 


118.10 


123.04 


NP-S20 


150.63 


221.42 


92.45 


90.63 


NP-S21 


149.20 


219.31 


91.57 


89.77 


NP-S22 


147.76 


217.20 


90.69 


88.90 


NP-S23 


146.33 


215.09 


89.80 


88.04 


NP-S24 


144.90 


212.98 


88.92 


87.18 


NP-S25 


143.46 


210.87 


88.04 


86.32 


NP-S26 


142.03 


208.77 


87.16 


85.45 


NP-S27 


140.59 


206.66 


86.28 


84.59 


NP-S28 


139.16 


204.55 


85.40 


83.73 


NP-S29 


137.72 


202.44 


84.52 


82.86 


NP-S30 


136.29 


200.33 


83.64 


82.00 


NP-S31 


134.85 


198.22 


82.76 


81.14 


NP-S32 


671.00 


1193.34 


339.84 


288.08 


NP-S33 


639.05 


1136.52 


323.66 


274.36 


NP-S34 


607.10 


1079.69 


307.48 


260.64 


NP-S35 


58.78 


162.05 


59.34 


63.25 


NP-S36 


56.11 


154.68 


56.64 


60.38 


NP-S37 


53.44 


147.32 


53.94 


57.50 


NP-S38 


50.77 


139.95 


51.25 


54.63 


NP-S39 


48.10 


132.59 


48.55 


51.75 


NP-S40 


53.44 


53.45 


31.86 


35.11 


NP-S41 


35.35 


63.65 


49.28 


61.33 



288 



Table E-3 (cont.) 



NP-S42 


34.48 


62.10 


48.08 


59.84 


NP-S43 


33.62 


60.55 


46.88 


58.34 


NP-S44 


29.93 


60.07 


25.01 


23.15 


NP-S45 


33.26 


66.75 


27.79 


25.72 


NP-S46 


36.59 


73.42 


30.57 


28.30 


NP-S47 


198.48 


237.84 


84.90 


72.28 


NP-S48 


180.43 


216.22 


77.18 


65.71 


NP-S49 


171.41 


205.41 


73.32 


62.42 


NP-S50 


162.39 


194.60 


69.46 


59.14 


NP-S51 


37.78 


59.52 


39.85 


42.50 


NP-S52 


34.00 


53.56 


35.87 


38.25 


NP-S53 


37.78 


59.52 


39.85 


42.50 


NP-S54 


41.56 


65.47 


43.84 


46.75 


SP-Sl 


237.60 


313.25 


133.41 


100.32 


SP-S2 


195.97 


296.99 


116.55 


79.27 


SP-S3 


244.11 


369.42 


127.89 


137.86 


SP-S4 


327.44 


507.40 


172.37 


167.21 



289 



Table E-4 Summary nominal capacity of driven pile in Cohesive Soil from North, Central and South of 



Vietnam by different method 

Data from North, Central and South of Vietnam 





a-Tomlinson method 


a- API method 


X method 


R- 
P 

Burland 
method 


Schmertma 
nn SPT 


Su-Terzaghi, 
Peck 


Su- 
Hara 


Su-Terzaghi, 
Peck 


Su- 
Hara 


Su-Terzaghi, 
Peck 


Su- Hara 


Ql 


Q2 


Q3 


Q4 


Q5 


Q6 


Q7 


Q8 


NP-Cl 


35.8 


71.6 


22.5 


46.3 


28.4 


58.4 


21.6 


38.3 


NP-C2 


32.5 


65.1 


20.5 


42.1 


25.8 


53.1 


19.6 


34.8 


NP-C3 


88.2 


166.8 


68.2 


122.5 


67.3 


124.1 


74.3 


101.9 


NP-C4 


84.2 


159.2 


65.1 


116.9 


64.3 


118.5 


70.9 


97.3 


NP-C5 


80.2 


151.6 


62.0 


111.4 


61.2 


112.8 


67.5 


92.7 


NP-C6 


76.2 


144.0 


58.9 


105.8 


58.1 


107.2 


64.2 


88.0 


NP-C7 


72.1 


136.4 


55.8 


100.2 


55.1 


101.6 


60.8 


83.4 


NP-C8 


144.6 


196.9 


116.8 


175.2 


106.5 


159.6 


147.4 


130.5 


NP-C9 


152.6 


207.8 


123.3 


184.9 


112.5 


168.5 


155.6 


137.8 


NP-Cl 


160.7 


218.8 


129.8 


194.6 


118.4 


177.3 


163.8 


145.0 


NP-Cll 


176.7 


240.6 


142.8 


214.1 


130.2 


195.1 


180.2 


159.5 


NP-C12 


168.7 


229.7 


136.3 


204.4 


124.3 


186.2 


172.0 


152.3 


NP-Cl 3 


184.8 


251.6 


149.3 


223.8 


136.1 


203.9 


188.4 


166.8 


NP-C14 


53.6 


71.6 


40.2 


71.2 


45.4 


86.4 


48.4 


59.3 


NP-C15 


51.0 


68.2 


38.3 


67.8 


43.2 


82.3 


46.1 


56.5 


NP-Cl 6 


48.5 


64.8 


36.4 


64.5 


41.1 


78.2 


43.8 


53.6 


NP-C17 


15.9 


23.6 


11.4 


24.7 


14.8 


30.5 


13.5 


20.6 


NP-Cl 8 


17.5 


26.0 


12.5 


27.2 


16.3 


33.6 


14.9 


22.7 


NP-Cl 9 


17.9 


25.5 


12.5 


26.2 


15.9 


32.2 


13.5 


22.1 


NP-C20 


19.6 


28.1 


13.8 


28.8 


17.5 


35.4 


14.9 


24.3 


NP-C21 


115.5 


152.9 


56.6 


182.1 


96.3 


173.0 


123.8 


121.5 


NP-C22 


109.7 


145.2 


53.8 


172.9 


91.5 


164.4 


117.6 


115.5 


NP-C23 


77.9 


79.2 


78.3 


89.6 


74.6 


82.1 


89.6 


55.8 


NM-C24 


76.5 


133.0 


51.8 


95.7 


71.4 


129.7 


66.8 


88.0 


NM-C25 


80.7 


140.4 


54.7 


101.0 


75.4 


136.9 


70.5 


92.9 


NM-C26 


93.5 


162.5 


63.3 


116.9 


87.3 


158.5 


81.7 


107.6 


NM-C27 


85.0 


147.7 


57.5 


106.3 


79.3 


144.1 


74.2 


97.8 


NM-C28 


106.6 


143.0 


67.8 


216.2 


136.6 


234.3 


137.2 


155.8 


NM-C29 


112.5 


151.0 


71.5 


228.2 


144.1 


247.3 


144.8 


164.5 


NM-C30 


118.5 


158.9 


75.3 


240.2 


151.7 


260.3 


152.4 


173.1 


NM-C3 1 


124.4 


166.9 


79.1 


252.2 


159.3 


273.4 


160.1 


181.8 


NM-C32 


130.3 


174.8 


82.8 


264.2 


166.9 


286.4 


167.7 


190.5 


NM-C33 


50.6 


79.9 


40.4 


66.2 


47.8 


82.2 


41.5 


85.5 


NM-C34 


47.9 


75.7 


38.2 


62.7 


45.3 


77.9 


39.4 


81.0 


NM-C35 


53.3 


84.1 


42.5 


69.7 


50.4 


86.6 


43.7 


90.0 


NM-C36 


55.9 


88.3 


44.6 


73.2 


52.9 


90.9 


45.9 


94.5 


NM-C37 


58.6 


92.5 


46.7 


76.6 


55.4 


95.2 


48.1 


99.0 


NM-C38 


61.2 


96.7 


48.9 


80.1 


57.9 


99.5 


50.3 


103.5 


CP-Cl 


36.7 


67.6 


48.9 


79.2 


55.0 


96.9 


36.8 


83.9 


CP-C2 


37.7 


69.4 


50.2 


81.2 


56.4 


99.4 


37.8 


86.1 


CP-C3 


38.7 


71.2 


51.5 


83.3 


57.9 


102.0 


38.7 


88.3 


CP-C4 


39.6 


72.9 


52.8 


85.4 


59.3 


104.5 


39.7 


90.5 


CP-C5 


40.6 


74.7 


54.1 


87.5 


60.8 


107.1 


40.7 


92.7 



290 



Table E-4 (cont.) 



CP-C6 


153.3 


151.4 


87.0 


162.6 


91.1 


176.4 


89.1 


127.4 


CP-C7 


157.3 


155.4 


89.3 


166.9 


93.5 


181.1 


91.5 


130.7 


CP-C8 


161.4 


159.3 


91.6 


171.2 


95.9 


185.7 


93.8 


134.1 


CP-C9 


165.4 


163.3 


93.9 


175.4 


98.3 


190.4 


96.2 


137.4 


CP-CIO 


169.4 


167.3 


96.2 


179.7 


100.7 


195.0 


98.5 


140.8 


CP-Cll 


















SP-Cl 


167.9 


286.7 


150.2 


244.3 


140.2 


233.5 


176.0 


195.1 


SP-C2 


106.5 


111.8 


129.7 


175.5 


116.1 


177.0 


168.6 


70.3 



291 



o 



G 



X! 



(33 

> 

O 
J= 

O 
00 

C 



a 
U 



o 

z; 



o 
-a 

X 



c 
> 
-a 



(33 
CJ 

c 



o 
c 

(Si 



3 

00 

H 



CO- i5 T3 
=! O 



e 



"a 
o 



a o 



OB 



O ro 

IN LTl 

ro ro 



op 



ro Ln 
rvi rvi 



ro 00 



rsi Qj 



rvj (X) 



T3 

o 



ro Ln 
O rvi 
rsl rsl 



e 



B O 



q 

cri 00 
U3 cn 
rsi rsi 



00 

5 a 



O CD 
00 CD 



00 

5 a 



^ ro 

ro U3 
rvi rvi 



rq rq 
(X) ^-i 



292 



213.1 


223.7 


234.4 


183.0 


178.6 


174.3 


169.9 


165.6 


161.2 


305.9 


278.1 


250.3 


236.4 


222.5 


57.2 


58.8 


60.3 


61.8 


63.4 


64.9 


66.5 


45.2 


86.1 


93.2 


130.2 


134.0 


75.1 


83.4 


91.7 


77.5 


70.5 


37.1 


33.8 


30.4 


26.1 


28.8 


152.5 


160.1 


167.8 


370.2 


361.4 


352.6 


343.8 


334.9 


326.1 


1100.2 


1000.2 


900.2 


850.2 


800.1 


80.9 


83.1 


85.3 


87.5 


89.6 


91.8 


94.0 


63.1 


147.3 


147.3 


237.3 


243.3 


98.5 


109.5 


120.4 


198.4 


180.4 


32.6 


29.7 


26.7 


43.3 


47.9 


267.4 


280.8 


294.1 


388.3 


379.0 


369.8 


360.5 


351.3 


342.0 


1101.7 


1001.6 


901.4 


851.4 


801.3 


109.8 


112.7 


115.7 


118.7 


121.6 


124.6 


127.6 


77.5 


164.5 


150.1 


274.5 


270.8 


107.1 


119.0 


130.9 


198.4 


180.4 


43.7 


39.7 


35.7 


43.3 


47.9 


145.5 


152.7 


160.0 


362.7 


354.0 


345.4 


336.7 


328.1 


319.5 


1079.2 


981.1 


883.0 


833.9 


784.9 


84.6 


86.9 


89.1 


91.4 


93.7 


96.0 


98.3 


65.3 


136.5 


129.1 


242.2 


251.0 


98.4 


109.3 


120.2 


198.4 


180.4 


35.9 


32.6 


29.4 


43.3 


47.9 


256.8 


269.6 


282.4 


390.8 


381.5 


372.2 


362.9 


353.6 


344.3 


1118.4 


1016.7 


915.0 


864.2 


813.4 


97.2 


99.8 


102.4 


105.0 


107.7 


110.3 


112.9 


74.7 


161.1 


161.8 


268.1 


265.4 


105.9 


117.6 


129.4 


198.4 


180.4 


39.1 


35.5 


32.0 


43.3 


47.9 


143.0 


150.2 


157.3 


364.8 


356.1 


347.4 


338.7 


330.0 


321.4 


1090.9 


991.7 


892.6 


843.0 


793.4 


79.4 


81.6 


83.7 


85.9 


88.0 


90.2 


92.3 


64.8 


134.1 


134.8 


241.7 


250.1 


98.0 


108.8 


119.7 


198.4 


180.4 


34.4 


31.3 


28.2 


43.3 


47.9 


198.4 


208.3 


218.3 


424.7 


414.6 


404.4 


394.3 


384.2 


374.1 


1092.3 


993.0 


893.7 


844.1 


794.4 


107.4 


110.3 


113.2 


116.1 


119.0 


121.9 


124.8 


76.2 


205.7 


207.0 


298.5 


286.9 


103.9 


115.5 


127.0 


198.4 


180.4 


43.6 


39.6 


35.7 


43.3 


47.9 


202.3 


212.4 


222.5 


381.1 


372.0 


362.9 


353.9 


344.8 


335.7 


1096.1 


996.5 


896.8 


847.0 


797.2 


94.8 


97.3 


99.9 


102.4 


105.0 


107.6 


110.1 


73.8 


146.6 


147.6 


266.9 


268.5 


104.2 


115.7 


127.3 


198.4 


180.4 


39.8 


36.2 


32.6 


43.3 


47.9 


152.5 


160.1 


167.8 


320.0 


312.3 


304.7 


297.1 


289.5 


281.9 


689.6 


626.9 


564.2 


532.9 


501.5 


51.0 


52.4 


53.8 


55.2 


56.5 


57.9 


59.3 


44.7 


111.4 


119.7 


201.6 


186.1 


50.9 


56.5 


62.2 


150.6 


136.9 


34.7 


31.6 


28.4 


31.9 


35.3 


267.4 


280.8 


294.1 


338.0 


330.0 


321.9 


313.9 


305.8 


297.8 


691.2 


628.3 


565.5 


534.1 


502.7 


79.9 


82.0 


84.2 


86.4 


88.5 


90.7 


92.8 


59.1 


128.7 


122.5 


238.7 


213.6 


59.5 


66.1 


72.7 


150.6 


136.9 


45.8 


41.6 


37.4 


31.9 


35.3 


145.5 


152.7 


160.0 


312.4 


305.0 


297.5 


290.1 


282.7 


275.2 


668.6 


607.8 


547.0 


516.6 


486.3 


54.7 


56.2 


57.6 


59.1 


60.6 


62.1 


63.6 


46.9 


100.6 


101.5 


206.5 


193.9 


50.7 


56.3 


62.0 


150.6 


136.9 


38.0 


34.5 


31.1 


31.9 


35.3 


256.8 


269.6 


282.4 


340.5 


332.4 


324.3 


316.2 


308.1 


300.0 


707.8 


643.4 


579.1 


546.9 


514.7 


67.3 


69.1 


70.9 


72.7 


74.6 


76.4 


78.2 


56.4 


125.2 


134.2 


232.3 


208.2 


58.2 


64.7 


71.1 


150.6 


136.9 


41.2 


37.4 


33.7 


31.9 


35.3 


143.0 


150.2 


157.3 


314.5 


307.0 


299.6 


292.1 


284.6 


277.1 


680.3 


618.5 


556.6 


525.7 


494.8 


49.6 


50.9 


52.3 


53.6 


54.9 


56.3 


57.6 


46.5 


98.3 


107.2 


205.9 


192.9 


50.3 


55.9 


61.5 


150.6 


136.9 


36.5 


33.2 


29.9 


31.9 


35.3 


198.4 


208.3 


218.3 


374.4 


365.5 


356.6 


347.7 


338.8 


329.8 


681.7 


619.8 


557.8 


526.8 


495.8 


77.5 


79.6 


81.7 


83.8 


85.8 


87.9 


90.0 


79.1 


169.8 


179.4 


262.7 


229.8 


56.3 


62.5 


68.8 


150.6 


136.9 


45.7 


41.5 


37.4 


31.9 


35.3 


202.3 


212.4 


222.5 


330.8 


323.0 


315.1 


307.2 


299.3 


291.5 


685.6 


623.2 


560.9 


529.7 


498.6 


64.9 


66.6 


68.4 


70.1 


71.9 


73.6 


75.4 


55.4 


110.8 


120.0 


231.2 


211.3 


56.5 


62.8 


69.1 


150.6 


136.9 


41.9 


38.1 


34.3 


31.9 


35.3 


M28 


M29 


M30 


M31 


M32 


M33 


M34 


M35 


M36 


M41 


M42 


M43 


M44 


M45 


M46 


M47 


M48 


M49 


M50 


M51 


M52 


M53 


M54 


M55 


M56 


M57 


M58 


M59 


09IAI 


T9IAI 


M62 


M63 


M64 


S9IAI 


99IAI 


M67 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 



293 



69.7 


73.3 


77.0 


92.4 


94.9 


97.3 


102.2 


178.3 


187.7 


197.0 


174.9 


58.0 


52.5 


63.6 


57.6 


55.2 


50.0 


68.5 


75.7 


28.6 


31.6 


63.3 


66.7 


70.0 


68.9 


72.5 


76.1 


44.9 


49.6 


178.0 


165.2 


61.1 


67.9 


74.7 


137.3 


135.3 


152.7 


160.7 


168.8 


107.7 


110.6 


113.4 


119.1 


447.8 


471.3 


494.9 


138.6 


160.5 


145.2 


73.7 


66.7 


260.6 


235.8 


59.3 


65.5 


50.4 


55.7 


159.0 


167.4 


175.8 


103.5 


108.9 


114.3 


69.5 


76.9 


370.6 


336.3 


53.3 


59.2 


65.1 


394.9 


399.9 


152.7 


160.7 


168.8 


104.8 


107.6 


110.3 


115.8 


376.9 


396.7 


416.6 


138.6 


168.3 


152.3 


101.4 


91.8 


260.1 


235.3 


75.3 


83.3 


50.4 


55.7 


140.4 


147.8 


155.2 


142.4 


149.9 


157.4 


86.6 


95.8 


266.1 


244.0 


67.9 


75.5 


83.0 


349.3 


352.1 


152.7 


160.7 


168.8 


64.8 


66.5 


68.2 


71.6 


319.7 


336.5 


353.3 


138.6 


147.2 


133.1 


82.7 


74.9 


252.3 


228.3 


57.2 


63.2 


50.4 


55.7 


121.9 


128.3 


134.8 


113.7 


119.6 


125.6 


73.1 


80.8 


174.4 


159.2 


47.8 


53.1 


58.4 


322.3 


326.6 


152.7 


160.7 


168.8 


152.7 


156.7 


160.7 


168.8 


427.7 


450.2 


472.7 


138.6 


175.7 


159.0 


88.3 


79.9 


264.2 


239.1 


72.4 


80.0 


50.4 


55.7 


160.4 


168.9 


177.3 


122.1 


128.5 


134.9 


81.1 


89.6 


317.7 


292.4 


67.4 


74.9 


82.4 


373.9 


376.4 


152.7 


160.7 


168.8 


84.9 


87.1 


89.4 


93.8 


350.9 


369.4 


387.9 


138.6 


155.0 


140.2 


76.6 


69.3 


255.6 


231.3 


54.5 


60.2 


50.4 


55.7 


131.1 


138.0 


144.9 


104.9 


110.4 


115.9 


71.2 


78.7 


219.3 


200.8 


47.2 


52.5 


57.7 


335.8 


339.8 


152.7 


160.7 


168.8 


183.0 


187.8 


192.6 


202.2 


351.2 


369.7 


388.2 


138.6 


152.0 


137.5 


86.5 


78.3 


260.4 


235.6 


83.1 


91.9 


52.5 


58.0 


138.8 


146.1 


153.4 


119.8 


126.1 


132.4 


96.2 


106.4 


504.3 


466.3 


53.2 


59.1 


65.0 


364.1 


361.7 


152.7 


160.7 


168.8 


114.5 


117.5 


120.5 


126.6 


363.3 


382.4 


401.5 


138.6 


142.4 


128.8 


85.4 


77.3 


257.0 


232.5 


67.1 


74.1 


50.4 


55.7 


129.8 


136.6 


143.4 


123.9 


130.4 


136.9 


79.6 


87.9 


207.5 


191.9 


48.3 


53.7 


59.0 


331.3 


333.5 


113.1 


119.1 


125.0 


111.0 


113.9 


116.9 


122.7 


384.8 


405.0 


425.3 


145.7 


96.2 


87.1 


40.5 


36.6 


94.0 


85.1 


61.3 


67.7 


25.7 


28.4 


127.7 


134.4 


141.2 


48.9 


51.5 


54.1 


42.7 


47.2 


377.7 


343.3 


48.1 


53.4 


58.7 


311.0 


289.3 


113.1 


119.1 


125.0 


113.1 


116.1 


119.0 


125.0 


313.9 


330.4 


347.0 


232.5 


104.1 


94.2 


68.2 


61.7 


93.5 


84.6 


77.4 


85.5 


25.7 


28.4 


109.1 


114.8 


120.6 


87.9 


92.5 


97.1 


59.8 


66.1 


285.2 


263.0 


67.9 


75.5 


83.0 


265.4 


241.5 


113.1 


119.1 


125.0 


68.1 


69.8 


71.6 


75.2 


256.7 


270.2 


283.7 


168.6 


82.9 


75.0 


49.5 


44.8 


85.8 


77.6 


59.2 


65.4 


25.7 


28.4 


90.6 


95.4 


100.1 


59.1 


62.2 


65.3 


46.2 


51.1 


181.5 


166.2 


42.6 


47.3 


52.0 


238.4 


216.0 


113.1 


119.1 


125.0 


88.2 


90.6 


92.9 


97.5 


364.7 


383.9 


403.1 


218.3 


111.5 


100.9 


55.1 


49.8 


97.6 


88.3 


74.4 


82.2 


25.7 


28.4 


129.1 


135.9 


142.7 


67.5 


71.1 


74.7 


54.2 


59.9 


336.7 


311.4 


42.0 


46.7 


51.3 


290.0 


265.8 


113.1 


119.1 


125.0 


88.2 


90.5 


92.8 


97.4 


287.9 


303.1 


318.2 


162.1 


90.7 


82.1 


43.4 


39.3 


89.0 


80.5 


56.5 


62.4 


25.7 


28.4 


99.7 


105.0 


110.2 


50.3 


53.0 


55.6 


44.3 


49.0 


226.3 


207.9 


42.0 


46.7 


51.3 


251.9 


229.2 


113.1 


119.1 


125.0 


191.3 


196.3 


201.3 


211.4 


288.2 


303.4 


318.6 


221.3 


87.8 


79.4 


53.3 


48.2 


93.8 


84.8 


85.2 


94.1 


27.8 


30.7 


107.5 


113.1 


118.8 


65.3 


68.7 


72.1 


69.4 


76.7 


523.3 


485.3 


47.9 


53.3 


58.6 


280.3 


251.1 


113.1 


119.1 


125.0 


117.8 


120.9 


124.0 


130.2 


300.3 


316.1 


331.9 


133.5 


78.2 


70.7 


52.2 


47.2 


90.4 


81.8 


69.1 


76.4 


25.7 


28.4 


98.5 


103.6 


108.8 


69.3 


73.0 


76.6 


52.7 


58.2 


214.6 


198.9 


43.1 


47.9 


52.6 


247.4 


222.9 


89IAI- 


69IAI- 


M70 


TZ.IAI- 


M72 


M73 


M74 


M75 


M76 


M77 


-M78 


T8IAI 


M82 


M83 


M84 


M85 


98IAI 


M87 


88IAI- 


68IAI- 


06IAI- 


T6IAI- 


M92 


M93 


M94 


M95 


96IAI- 


M97 


86IAI 


66IAI- 


M102 


M103 


M104 


M105 


M106 


M107 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


IAIN 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP- 


NP-I 


NP-I 


NP-I 


NP-I 


NP-I 


NP-I 



294 



c 
o 
o 

in 

m 
3 

(33 

H 



295 



(33 

H 



105.5 


107.5 


72.3 


76.3 


80.3 


88.3 


102.8 


105.0 


107.2 


109.5 


111.7 


113.9 


116.2 


118.4 


120.7 


75.4 


77.0 


78.6 


81.8 


85.0 


348.3 


385.0 


73.8 


77.9 


82.0 


90.2 


165.0 


141.8 


189.5 


181.8 


89.0 


173.2 


82.9 


84.5 


83.4 


88.0 


92.6 


101.9 


296.2 


302.7 


309.1 


315.5 


322.0 


328.4 


334.9 


341.3 


347.7 


58.9 


60.1 


61.4 


63.9 


66.4 


871.9 


963.7 


87.3 


92.2 


97.0 


106.7 


377.0 


392.4 


201.5 


453.7 


378.8 


501.8 




Ln 


IN 


00 


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Ln 


rvi 


l-v. 


r-i 


Ln 


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rvi 
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rvi 
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rvi 

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LD 

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rA 

cn 
rvi 


Lfi 

Ln 


LD 
1^ 

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00 


80.2 


81.7 


62.5 


66.0 


69.4 


76.4 


296.2 


302.7 


309.1 


315.5 


322.0 


328.4 


334.9 


341.3 


347.7 


66.6 


68.0 


69.5 


72.3 


75.1 


671.3 


741.9 


94.2 


99.4 


104.7 


115.1 


340.7 


362.4 


175.5 


451.5 


365.2 


465.9 




r-l 


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rvi 
O 
Ln 


79.8 


81.3 


67.0 


70.7 


74.4 


81.9 


296.2 


302.7 


309.1 


315.5 


322.0 


328.4 


334.9 


341.3 


347.7 


62.0 


63.4 


64.7 


67.3 


70.0 


732.4 


809.5 


89.2 


94.2 


99.2 


109.1 


354.3 


371.7 


178.9 


453.2 


371.8 


482.1 


IN 


r-. 




IN 




LD 


rvi 


l-v. 


r-i 


Ln 


q 




Ol 


rq 


l-v. 


rvi 


00 


■* 


LD 


CTl 


LD 


rvj 


CTl 


LD 


rvj 






rvi 




q 




q 


d 
m 


IN 

cn 

<H 


00 
IN 


Lfi 

ro 

r^ 


rvi 

r^ 


LD 
Ln 


LD 
Ol 
rvi 


rvi 
O 
ro 


ai 
o 
ro 


Lfi 
r^ 

cn 


rvi 
rv| 
ro 


00 

rvi 
ro 


ro 
ro 


r-i 

ro 


l-v^ 

ro 


LD 




ui 


rvi 
00 


Lfi 

00 


rvi 
in 
<a 


rA 

rM 


LD 

ro 

r^ 


r^ 


rvi 
Ln 

r^ 


LD 
r^ 


LD 

ro 


d 
ro 


oi 

00 

r^ 


Lfi 

LD 


ui 

LD 

ro 


i-v^ 

CTl 


95.0 


96.9 


78.7 


83.0 


87.4 


96.1 


296.2 


302.7 


309.1 


315.5 


322.0 


328.4 


334.9 


341.3 


347.7 


66.9 


68.3 


69.7 


72.6 


75.4 


653.9 


722.8 


104.0 


109.8 


115.5 


127.1 


343.0 


368.5 


166.1 


454.9 


369.0 


482.1 


93.1 


94.9 


78.4 


82.7 


87.1 


95.8 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


54.1 


55.3 


56.4 


58.7 


61.0 


788.2 


871.2 


61.6 


65.0 


68.5 


75.3 


266.6 


295.2 


189.5 


291.8 


272.5 


369.0 




ai 


IN 


Ln 


00 




Ln 




l-v. 


ro 




Ln 


r-i 


1^ 


ro 


ID 


Ln 


Ln 








rq 




l-v. 


1^ 


00 


rvi 


r-. 




o 


LD 


Ln 


ai 


IN 


Lfi 
Ol 


d 
o 

r^ 


Lfi 

o 


LD 


Lfi 

ID 


oi 


rvi 
1^ 


LD 
1^ 


ai 
1^ 


rri 

00 


00 


d 

ai 


ai 


rvi 
Ol 


CTl 


LD 
CTl 


d 
o 

r^ 


o 

r^ 


LD 


Lfi 

1^ 


d 

CTl 


Lfi 
CTl 


d 
o 

r^ 


d 

r^ 
r^ 


Ln 
rvi 


rA 
00 

rvi 


ui 
rvi 


CTI 

rvi 


d 
rvi 


rri 
Ln 
ro 


90.4 


92.1 


57.5 


60.7 


63.9 


70.3 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


61.9 


63.2 


64.5 


67.1 


69.8 


587.6 


649.4 


68.5 


72.3 


76.1 


83.7 


230.3 


265.2 


163.4 


289.6 


258.9 


333.2 


117.3 


119.6 


99.0 


104.5 


110.0 


121.0 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


80.0 


81.7 


83.4 


86.8 


90.2 


757.4 


837.2 


78.4 


82.7 


87.1 


95.8 


275.4 


296.3 


249.1 


296.1 


279.5 


370.1 


90.0 


91.7 


62.0 


65.4 


68.9 


75.8 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


57.3 


58.5 


59.7 


62.2 


64.6 


648.7 


717.0 


63.5 


67.1 


70.6 


77.7 


243.9 


274.5 


166.9 


291.4 


265.5 


349.4 








o 


00 


Ln 


Ln 




l-v. 


ro 


ai 


Ln 


r-i 


r-v 


ro 




CTl 


^ 


Ln 


Ln 


CTl 


r-. 


rvi 




LD 


o 


o 


q 


r-i 


r-i 


r-i 


rM 


d 


cn 
t 

r^ 


cn 

IN 
r^ 


d 

ro 

r^ 


LD 

ro 

r^ 


d 
Ln 


Lfi 

ID 


oi 


rvi 
r-v 

r^ 


LD 
r-i 


ai 

r-i 


rri 

00 
r^ 


00 


d 

CTl 


CTl 


rA 


rvi 
1^ 


1^ 


1^ 


d 

00 


00 
ID 

Ln 


00 

rvi 

ID 


111, 


r^ 
r^ 


rri 
rvi 

r^ 


LD 
ro 


LD 
LD 
rvi 


rri 
rvi 




rri 
O 
ro 


rri 
LD 
rv| 


ID 

cn 


105.2 


107.3 


73.7 


77.7 


81.8 


90.0 


165.5 


169.1 


172.7 


176.3 


179.9 


183.5 


187.1 


190.7 


194.3 


62.1 


63.4 


64.8 


67.4 


70.1 


570.2 


630.3 


78.3 


82.6 


87.0 


95.7 


232.5 


271.3 


134.4 


293.1 


262.7 


349.4 


CP-M38 


CP-M39 


CP-M40 


CP-M41 


CP-M42 


CP-M43 


SP-Ml 


SP-M2 


SP-M3 


SP-M4 


SP-M5 


SP-M6 


SP-M7 


SP-M8 


SP-M9 


SP-MIO 


SP-Mll 


SP-M12 


SP-M14 


SP-M16 


SP-M17 


SP-M18 


SP-M19 


SP-M20 


SP-M21 


SP-M22 


SP-M23 


SP-M24 


SP-M25 


SP-M26 


SP-M27 


SP-M28 



296 



APPENDIX F 
Histogram and Frequency Distribution of 
Bias Factor for Driven Piles from Vietnam 



Lamdal AllSand data 

Normal 

Lognormal 




Bias Factor 

Figure F-Sl-a Histogram and frequency distribution of bias factorXl for 58 cases of concrete 
piles in Sand using the Nordlund method (((): Peck, Hanson and Thombum) in Vietnam 




3 4 5 

Reliability Index, p 



Figure F-Sl-b Resistant factor calibration for 58 cases of concrete piles in Sand using the 
Nordlund method (cj): Peck, Hanson and Thornbum) in Vietnam 



297 



3.5 




0.5 1 1.5 

Bias Factor 



Figure F-Sl-c Histogram and frequency distribution of bias factor for Xl 54cases of concrete 
piles in Sand using the Nordlundmethod ((j): Peck, Hanson and Thornbum)in North of Vietnam 




0.1 I 1 1 — \ 1 1 1 1 1 1 

012345678 

Reliability Index, p 

Figure F-Sl-d Resistant factor caUbration for54 cases of concrete piles in Sand using 
theNordlundmethod (((): Peck, Hanson and Thombum)in North of Vietnam 



298 



2.5 
2 



0.5 







1 1 




1 












Lamdal SouthSand data 










X< ^ 

t 




Normal 














log-normal 








/ 

' / 
/ 

/ 

/ 




\ \ 


\ 




- 


/ / 


/ 

f 






N 
\ 

\ 






/ / 








\ 






/ / 








X ^ 
X ^ 
X ^ 
X ^ 






/ / 
/ / 








X ^ 
X ^ 
X ^ 
X \ 






/ ✓ 
/ / 

/ 








> 


\ 




























1 



0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 

Bias Factor 

Figure F-Sl-e Histogram and frequency distribution of bias factor W for 4 cases of concrete 
piles in Sand using the Nordlundmethod (cj): Peck, Hanson and Thornbum)in South of Vietnam 



299 



Lamda2AIISand data 

Normal 

Lognormal 



0.5 0.6 
Bias Factor 




0.9 



Figure F-S2-a: Histogram and frequency distribution of bias factor X2 for 58 cases of concrete 
piles in Sand using the Nordlund method (((): Schmertmann) in Vietnam 



e 



1 

0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 



0.2 



0.1 





2 3 
Reliability Index, p 



Figure F-S2-b Resistant factor calibration for 58 cases of concrete piles in Sand using the 
Nordlund method (((): Schmertmann) in Vietnam 



300 




Figure F-S2-C Histogram and frequency distribution of bias factor X2 for 54 cases of concrete 
piles in Sand using the Nordlundmethod (cj): Schmertmann)in North of Vietnam 




2 3 
Reliability Index, p 



Figure F-S2-d Resistant factor calibration for 54 cases of concrete piles in Sand using the 
Nordlundmethod ((j): Schmertmann)in North of Vietnam 



301 



10 



^ 6 

CO 

c 

0) 
Q 



Lamda2SouthSand data 
Normal distribution 
Lognormal distribution 




Figure F-S2-e Histogram and frequency distribution of bias factor X2 for 4 cases of concrete 
piles in Sand using the Nordlundmethod (((): Schmertmann)in South of Vietnam 



302 



LamdaSAIISand data 

Normal 

Log normal 




1.2 1.4 1.6 

Bias Factor 



2.2 



Figure F-S3-a: Histogram and frequency distribution of bias factor X3 for 58 cases of concrete 
piles in Sand using the Meyerhof SPT methodin Vietnam 




3 4 
Reliability Index, p 



Figure F-S3-b: Resistant factor calibration for 58 cases of concrete piles in Sand using the 
Meyerhof SPT methodin Vietnam 



303 



LamdaSNorthSand data 
Normal 
■ Log normal 




Figure F-S3-c: Histogram and frequency distribution of bias factor X3 for 54 cases of concrete 
piles in Sand using the Meyerhof SPT methodin North of Vietnam 



1^ 
0.9 - 
0.8 - 



e 



0.7 - 



(B 0.6 -_ 

o 

c 

ro 

■I 0.5- 



03 



0.4 - 

0.3 - 

0.2 - 
1 



4 5 
Reliability Index, p 



Figure F-S3-d Resistant factor calibration for 54 cases of concrete piles in Sand using the 
Meyerhof SPT methodin North of Vietnam 



304 




Figure F-S3-e Histogram and frequency distribution of bias factor 13 for 4 cases of concrete 
piles in Sand using the Meyerhof SPT methodin South of Vietnam 



305 



3.5 p 
3 - 
2.5 - 



2- 

w 

CD 

Q 



1.5 



Lamda4AIISand data 
Normal 
■ Lognormal 




0.4 0.6 0.8 



1 .2 1 .4 1 .6 
Bias Factor 



1.8 



Figure F-S4-a: Histogram and frequency distribution of bias factor X4 for 58 cases of concrete 
piles in Sand using the Schmertmann SPT methodin Vietnam 




Figure F-S4-b: Resistant factor calibration for 58 cases of concrete piles in Sand using the 
Schmertmann SPT methodin Vietnam 



306 




Figure F-S4-c: Histogram and frequency distribution of bias factor X4 for 54 cases of concrete 
piles in Sand using the Schmertmann SPT methodin North of Vietnam 




2.5 3 3.5 

Reliability Index, p 



5.5 



Figure F-S4-d: Resistant factor calibration for 54 cases of concrete piles in Sand using the 
Schmertmann SPT methodin North of Vietnam 



307 




Figure F-S4-e: Histogram and frequency distribution of bias factor X4 for 4 cases of concrete 
piles in Sand using the Schmertmann SPT methodin North of Vietnam 



308 



LamdalAIICIaydata 
Normal 
Log normal 




1.5 2 2.5 3 3.5 

Bias Factor 

Figure F-Cl-a: Histogram and frequency distribution of bias factor X\ for SOcases of concrete 
piles in Clay using the a-Tomlinson method (Su: Peck) in Vietnam 



1 r 

0.9 
0.8 



e 0.7 - 

o 

^ 0.6- 



o 



0.5 



in 
CD 

ir 0.4 



0.3 - 
0.2 - 



0.1 









Reliability Index, p 



Figure F-Cl-b: Resistant factor calibration for SOcases of concrete piles in Clay using the a- 
Tomlinson method (Su: Peck) in Vietnam 



309 




Bias Factor 



Figure F-Cl-c Histogram and frequency distribution ofkl for 38 cases of concrete piles in Clay 
using the a-Tomlinson method (Su: Peck) in Northof Vietnam 




Reliability Index, p 

Figure F-Cl-d Resistance factor calibration for 38 cases of concrete piles in Clay using the a- 
Tomlinson method (Su: Peck) in Northof Vietnam 



310 



T 




Bias Factor 

Figure F-Cl-e Histogram and frequency distribution ofkl for 10 cases of concrete piles in Clay 
using the a-Tomlinson method (Su: Peck) in Central of Vietnam 



1.1 




Reliability Index, p 



Figure F-Cl-f Resistance factor calibration for 10 cases of concrete piles in Clay using the a- 
Tomlinson method (Su: Peck) in Central of Vietnam 



311 



0.8 1 1 .2 

Bias Factor 



Lamda2AIIC lay data 
Normal 
■ Log normal 




1.8 



Figure F-C2-a Histogram and frequency distribution of bias factor Xl for SOcases of concrete 
piles in Clay using the a-Tomlinson method (Su: Hara) in Vietnam 




3 4 
Reliability Index, p 



Figure F-C2-b Resistance factor calibration for SOcases of concrete piles in Clay using the a- 
Tomlinson method (Su: Hara) in Vietnam 



312 



Lamda2NorthClay data 




Bias Factor 

Figure F-C2-C Histogram and frequency distribution of bias factor 12 for 38cases of concrete 
piles in Clay using the a-Tomlinson method (Su: Hara) in North of Vietnam 




■-1 1 2 3 4 5 6 



Reliability Index, p 

Figure F-C2-d Resistance factor calibration for 38cases of concrete piles in Clay using the a- 
Tomlinson method (Su: Hara) in North of Vietnam 



313 




Figure F-C2-e Histogram and frequency distribution of bias factor Xl for lOcases of concrete 
piles in Clay using the a-Tomlinson method (Su: Hara) in South of Vietnam 




Reliability Index, p 

Figure FigureF-C2-f Resistance factor calibration for lOcases of concrete piles in Clay using the 
a-Tomlinson method (Su: Hara) in South of Vietnam 



314 



0.8 

0.7 

0.6 

0.5 

I 0.4 
Q 

0.3 
0.2 
0.1 











0.5 



1.5 
Data 



LamdaSAIIClay data 
Normal 
■Log normal 



2.5 



Figure Figure F-C3-a Histogram and frequency distribution of bias factor X3 for 50cases of 
concrete piles in Clay using the a-API method (Su: Peck) in Vietnam 




0.2 
1.5 



2.5 



3.5 4 4.5 
Reliability Index, p 



5.5 



6.5 



Figure Figure F-C3-b: Resistance factor calibration for SOcases of concrete piles in Clay using 
the a-API method (Su: Peck) in Vietnam 



315 




Bias Factor 

Figure F-C3-a Histogram and frequency distribution of bias factor X3 for 38cases of concrete 
piles in Clay using the a-API method (Su: Peck) in North of Vietnam 




Reliability Index, p 



Figure F-C3-b Resistance factor calibration for 38cases of concrete piles in Clay using the a-API 
method (Su: Peck) in North of Vietnam 



316 











1 




1 




LamdaSCentralClay data 










Normal 














Lognormal 










- 


























// 
/ 






\ 

\\ 


1 













1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 

Bias Factor 

Figure F-C3-C Histogram and frequency distribution of bias factor Xh for lOcases of concrete 
piles in Clay using the a-API method (Su: Peck) in Central of Vietnam 




Figure F-C3-d Resistance factor calibration for lOcases of concrete piles in Clay using the a-API 
method (Su: Peck) in Central of Vietnam 



317 



LamdaSAIIC lay data 

Normmal 

Log normal 




1.2 1.4 1.6 
Bias Factor 



Figure F-C5-aHistogram and frequency distribution of bias factor X5 for SOcases of concrete 
piles in Clay using the ^method (Su: Peck) in Vietnam 




4 5 
Reliability Index, p 



Figure F-C5-b Resistance factor calibration for 50cases of concrete piles in Clay using the 
^method (Su: Peck) in Vietnam 



318 



LamdaSNorthClay data 

Normal 

Lognormal 




1 .2 1 .4 
Bias Factor 

Figure F-C5-C Histogram and frequency distribution of bias factor X5 for 38cases of concrete 
piles in Clay using the A,metliod (Su: Peck) North of Vietnam 



1.2p 
1.1 - 
1 - 
0.9 - 
0.8 - 



S 0-7- 
c 

CO — 

M 0.6 - 

U5 
CD 

^ 0.5- 

0.4- 

0.3 - 

0.2 L 




1 2 3 4 5 6 7 8 

Reliability Index, (3 

Figure F-C5-d Resistance factor calibration for 38cases of concrete piles in Clay using the 
A,method (Su: Peck) North of Vietnam 



319 



2 - 
1.8- 
1.6 
1.4 
>. 1-2h 
1 

0.8- 
0.6- 
0.4- 
0.2- 



</3 
CD 

Q 



LamdaSCentralC lay data 
Normal 
■ Lognormal 




Bias Factor 



Figure F-C5-e Histogram and frequency distribution of bias factor X5 for lOcases of concrete 
piles in Clay using the ^method (Su: Peck) Central of Vietnam 




1.5 



2.5 3 3.5 

Reliability Index, p 



4.5 



Figure F-C5-f Resistance factor calibration for lOcases of concrete piles in Clay using the 
^method (Su: Peck) Central of Vietnam 



320 



0.6 0.8 
Bias Factor 



Lamda6AIIC lay data 

Normal 

Lognormal 




1.4 



Figure F-C6-a Histogram and frequency distribution of bias factor 1.6 for SOcases of concrete 
piles in Clay using the ^method (Su: Hara) in Vietnam 




3 4 
Reliability Index, p 

Figure F-C6-b Resistance factor calibration for SOcases of concrete piles in Clay using the 
A-method (Su: Hara) in Vietnam 



321 



LamdaSNorthClay data 
Normal 
■ Log normal 




0.6 0.7 
Bias Factor 



Figure F-C6-cHistogram and frequency distribution of bias factor 'k6 for 38cases of concrete 
piles in Clay using the ^method (Su: Hara) in North of Vietnam 



1 

0.9 
0.8 
0.7 
0.6 
0.5 



S3 0.4 



0.3 
0.2 

0.1 



-1 





3 4 
Reliability Index, p 



Figure F-C6-d Resistance factor calibration for 38cases of concrete piles in Clay using the 
^method (Su: Hara) in North of Vietnam 



322 





1 








1 








Lamda6CentralClay data 












Normal 














- 


Lognormal 















































%.b 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 

Bias Factor 



Figure F-C6-eHistogram and frequency distribution of bias factor for lOcases of concrete 
piles in Clay using the ^method (Su: Hara) in South of Vietnam 



1.4 




Reliability Index, p 

Figure F-C6-f Resistance factor calibration for lOcases of concrete piles in Clay using the 
^method (Su: Hara) in South of Vietnam 



323 



Lamda7AIICIay data 

Normal 

Log normal 




1.2 1.4 
Bias Factor 



Figure F-C7-aHistogram and frequency distribution of bias factor Xl for 50 cases of concrete 
piles in Clay using the P methodin Vietnam 



1 

0.9 
0.8 
0.7 
0.6 
0.5 
0.4 - 
0.3 - 
0.2 
0.1 

123456789 

Reliability Index, p 

Figure F-C7-bResistance factor calibration of concrete piles in Clay using the P methodin 
Vietnam 



e 



o 
m 

0) 

o 
_cd 

03 



324 



Lamda7NorthClay data 

Normal 

Lognormal 




0.5 1 1.5 2 

Bias Factor 

Figure F-C7-cHistogram and frequency distribution of bias factor Xl for 38cases of concrete 
piles in Clay using the Pmethod in North of Vietnam 



1 p 
0.9 - 
0.8 - 



^.0.7 -_ 
o 

,?0.6- 



O 

§0.5- 
« 

^0.4- 



0.3 - 
0.2 - 
0.1. - 



4 5 
Reliability Index, p 



Figure F-C7-dResistance factor calibration of concrete piles in Clay using the Pmethod in North 
of Vietnam 



325 




0.9 1 

Bias Factor 



Figure F-C7-eHistogram and frequency distribution of bias factor Xl for lOcases of concrete 
piles in Clay using the Pmethod in Central of Vietnam 




3 4 
Reliability Index, p 



Figure F-C7-fResistance factor calibration of concrete piles in Clay using the Pmethod in Central 
of Vietnam 



326 



LamdaSAIICIaydata 
Normal 
■ Lognormal 




0.8 1 
Bias Factor 



Figure F-C8-a Histogram and frequency distribution of bias factor 18 for 50 cases of concrete 
piles in Clay using the Schmertmann SPT in Vietnam 




4 5 
Reliability Index, p 

Figure F-C8-bResistance factor calibration for 50 cases of concrete piles in Clay using the 
Schmertmann SPT in Vietnam 



327 



2 



1.5 



0.5 



LamdaSNorthClay data 

Normal 

Lognormal 



0.2 



0.4 



0.6 



0.8 1 
Bias Factor 



1.2 



1.4 



1.6 



1.8 



Figure F-C8-cHistogram and frequency distribution of bias factor X8 for 38 cases of concrete 
piles in Clay using the Schmertmann SPT in North of Vietnam 



0.8 

2- 0.7 - 
o 

i2 0.6 - 

CD 
O 

i 0-5 : 

% 0.4- 
0.3 
0.2 

°'^0 1 2 3 4 5 6 7 8 9 

Reliability Index, (3 

Figure F-C8-dResistance factor calibrationfor 38 cases of concrete piles in Clay using the 
Schmertmann SPT in North of Vietnam 




328 




1.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 

Bias Factor 



Figure F-C8-eHistogram and frequency distribution of bias factor X8 for 10 cases of concrete 
piles in Clay using the Schmertmann SPT in South of Vietnam 



329 



1.8 




0.5 1 1.5 

Bias Factor 



Figure F-Ml-a Histogram and frequency distribution of bias factor A.1 for 165 cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Peck, (j): Peck, Hanson and 
Thornburn) in Vietnam 



e 

O 

■4— ' 

O 
CO 
LL 

CD 
O 

CC 

•4—* 

'(/) 
CD 

cr 



0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 








3 4 5 

Reliability Index, p 



8 



Figure F-Ml-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Peck, (j): Peck, Hanson and Thornburn) in Vietnam 



330 



1.8 




0.5 1 1.5 

Bias Factor 



Figure F-Ml-cHistogram and frequency distribution of bias factor A.1 for 99 cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Peck, (j): Peck, Hanson and 
Thornburn) in North of Vietnam 




Reliability Index, p 

Figure F-Ml-dResistance factor calibration for 99 cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thornburn) in North of 
Vietnam 



331 




Bias Factors 

Figure F-Ml-e Histogram and frequency disfribution of bias factor XI for 4 leases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Peck, (j): Peck, Hanson and 
Thornbum) in Central of Vietnam 




Reliability Index, (3 

Figure F-Ml-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thornbum) in Central of 
Vietnam 



332 



Lamdal SouthMixed data 

Normal 

Log normal 




1 1.2 
Bias Factor 

Figure F-Ml-gHistogram and frequency distribution of bias factor A.1 for 25cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Peck, (j): Peck, Hanson and 
Thornbum) in South of Vietnam 

1 

0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 



© 

o 
o 

LL 

0} 
O 
c 

B 

en 
DC 








3 4 
Reliability Index, p 



6 



Figure F-Ml-hResistance factor calibration for 25cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thomburn) in South of 
Vietnam 



333 



T 



1 .6 - Lamda2AIIMixed data 

Normal 




Log-Normal 



0.5 1 1.5 2 2.5 3 

Bias Factor 

Figure F-M2-aHistogram and frequency distribution of bias factor A.2 for 165 cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and 
Thornburn) in Vietnam 




Q -| I \ \ \ \ I \ I I \ 

-0.5 0.5 1 1.5 2 2.5 3 3.5 4 

Reliability Index, p 

Figure F-M2-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thornburn) in Vietnam 



334 




0.4 0.6 0.8 1 1.2 1.4 

Bias Factor 



Figure F-M2-cHistogram and frequency distribution of bias factor A.2 for 99cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and 
Thornburn) in North of Vietnam 




Reliability Index, p 

Figure F-M2-dResistance factor calibration for 99cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thornburn) in North of 
Vietnam 



335 




0.2 0.4 0.6 0.8 1 1.2 1.4 

Bias Factor 



Figure F-M2-eHistogram and frequency distribution of bias factor A.2 for 41 cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Hara, cj): Peck, Hanson and 
Thombum) in Central of Vietnam 




1 2 

Reliability Index, p 



Figure F-M2-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thomburn) in Central of 
Vietnam 



336 



2.5 



1.5- 



co 
c 

CD 

a 



Lamda2SouthMixecl data 

Normal 

Log-normal 



0.5 




Bias Factor 

Figure F-M2-g Histogram and frequency distribution of bias factor A.2 for 25 cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and 
Thornburn) in South of Vietnam 




Reliability Index, p 

Figure F-M2-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using the a- 
Tomlinson and Nordlund/Thurman method (Su: Hara, (j): Peck, Hanson and Thornburn) in South of 
Vietnam 



337 



1.5 



LamdaSAIIMixed data 

Normal 

Log-Normal 




0.4 0.6 0.8 1 1.2 1.4 1.6 

Bias Factor 

Figure F-M3-aHistogram and frequency distribution of bias factor A.3 for 165 cases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) 
in Vietnam 




Reliability Index, (3 



Figure F-M3-b Resistance factor calibration for 165cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) in Vietnam 



338 




Figure F-M3-cHistogram and frequency distribution of bias factor A.3 for 99cases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) 
in North of Vietnam 



1 




0.1 I ^ ^ — \ \ ^ ^ ^ ^ 1 

01 2345678 

Reliability Index, (3 

Figure F-M3-dResistance factor calibration for 99cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Peck, cj): Peck, Hanson and Thombum) in North of Vietnam 



339 



LamdaSCentralMixed data 

Normal 

Log-normal 




0.5 1 1.5 2 

Bias Factor 

Figure F-M3-eHistogram and frequency distribution of bias factor A.3 for 4 leases of eonerete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) 
in Central of Vietnam 




1 2 3 4 5 6 7 8 

Reliability Index, p 



Figure F-M3-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Peck, (j): Peck, Hanson and Thombum) in Central of Vietnam 



340 



Lamda4SouthMixed data 

Normal 

Log normal 




0.8 1 1.2 
Bias Factor 

Figure F-M3-gHistogram and frequency distribution of bias factor A.3 for 25 cases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Peck, cj): Peck, Hanson and Thombum) 
in South of Vietnam 



1 r 

0.9 

0.8 

%.7 

o 

o 

^.6 

03 
O 

DC 

0.3 
0.2 
0.1 








Reliability Index, p 



Figure F-M3-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) in South of Vietnam 



341 




Bias Factor 

Figure F-M4-a Histogram and frequency distribution of bias factor X4 for 1 65 cases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Hara, (j): Peck, Hanson and Thombum) 
in Vietnam 




1 2 3 4 5 6 7 

Reliability Index, (3 

Figure F-M4-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Hara, ^: Peck, Hanson and Thombum) in Vietnam 



342 



LamdaSNorthMixed data 

Normal 

Log-Normal 




1 1.2 
Bias Factor 

Figure F-M4-cHistogram and frequency distribution of bias factor A.4 for 99 cases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Hara, (j): Peck, Hanson and Thombum) 
in North of Vietnam 



1 

0.9 
0.8 
0.7 
0.6 
0.5 



^ 0.4 



0.3 
0.2 
0.1 








1>3, 



3 4 5 

Reliability Index, (3 



Figure F-M4-dResistance factor calibration for 99cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Hara, (j): Peck, Hanson and Thombum) in North of Vietnam 



343 



2F 




0.4 0.6 0.8 1 1.2 1.4 1.6 

Bias Factor 



Figure F-M4-eHistogram and frequency distribution of bias factor A.4 for 41 cases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Hara, (j): Peck, Hanson and Thombum) 
in Central of Vietnam 




-1 1 2 3 4 5 6 



Reliability Index, p 

Figure F-M4-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thombum) in Central of Vietnam 



344 



Lamda4SouthMixed data 

Normal 

Log normal 




0.8 1 1 .2 
Bias Factor 

Figure F-M4-gHistogram and frequency distribution of bias factor A.4 for 25cases of concrete piles in 
Mixed soils using the a-API andNordlund/Thurman method (Su: Hara, (j): Peck, Hanson and Thombum) 
in South of Vietnam 



1 

0.9 
0.8 
0.7 
0.6 



to 
o 

5 0.5 





Reliability Index, (3 

Figure F-M4-h Resistance factor calibration for 25 cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thombum) in South of Vietnam 



345 



LamdaSAIIMixed data 

Normal 

Log-Normal 




1 1.2 1.4 

Bias Factor 

Figure F-M5-a Histogram and frequency distribution of bias factor A.5 for 165cases of concrete piles in 
Mixed soils using the 'k andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) in 
Vietnam 



1 

0.9 
0.8 
0.7 
0.6 
0.5 



oi 0.4 
0.3 
0.2 



01 2345678 

Reliability Index, p 

FigureF-M5-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the X 
andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) in Vietnam 



346 



LamdaSNorthMixed data 

Normal 

Log-Normal 




1 1.2 
Bias Factor 

FigureF-M5-c Histogram and frequency distribution of bias factor A.5 for 99 cases of concrete piles in 
Mixed soils using the X and Nordlund/Thurman method (Su: Peck, cj): Peck, Hanson and Thombum) in 
North of Vietnam 



0.9 
0.8 
0.7 
0.6 



O 

S 0.5 



Q) 
DC 



0.4 
0.3 
0.2 
0.1 









3 4 5 

Reliability Index, (3 



Figure F-M5-d Resistance factor calibration for 99 cases of concrete piles in Mixed soils using 
the X andNordlund/Thurman method (Su: Peck, Peck, Hanson and Thombum) in North of Vietnam 



347 




0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 

Bias Factor 



Figure F-M5-eHistogram and frequency distribution of bias factor A.5 for 41 cases of concrete piles in 
Mixed soils using the X andNordlund/Thurman method (Su: Peck, ((): Peck, Hanson and Thombum) in 
Central of Vietnam 




1 2 3 4 5 6 7 

Reliability Index, (3 



Figure F-M5-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the X 
andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) in Central of Vietnam 



348 





2 




1 .o 




1.6 




1.4- 




1.2 








1 - 


LJ 






0.8 - 




0.6 




0.4 




0.2 ' 








LamdaSSouthMixed data 

Normal 

Log-Normal 




1 1 .2 1 .4 
Bias Factor 



Figure F-M5-gHistogram and frequency distribution of bias factor A.5 for 25 cases of concrete piles in 
Mixed soils using the X andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) in 
South of Vietnam 



1 

0.9 
0.8 
0.7 
0.6 



CD 
O 

w 

'& 0.4 
cc 

0.3 
0.2 
0.1 








Reliability Index, p 



Figure F-M5-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using the X 
andNordlund/Thurman method (Su: Peck, (|): Peck, Hanson and Thombum) in South of Vietnam 



349 



Lamda6AIIMixed data 




0.2 0.4 0.6 0.8 1 1.2 1.4 

Bias Factor 



Figure F-M6-aHistogram and frequency distribution of bias factor 1.6 for 165 cases of concrete piles in 
Mixed soils using the X andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thombum) in 
Vietnam 




Reliability Index, p 



Figure F-M6-bResistance factor calibration for 165cases of concrete piles in Mixed soils using the X 
andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thombum) in Vietnam 



350 



2.5 



>-1.5 



CO 

Q 



0.5 



Lamda6NorthMixed data 
Normal 
■ Log-Normal 




0.8 1 
Bias Factor 



Figure F-M6-cHistogram and frequency distribution of bias factor X6 for 99 cases of concrete piles in 
Mixed soils using the X and Nordlund/Thurman method (Su: Hara, cj): Peck, Hanson and Thombum) in 
North of Vietnam 




0.3 
0.2 
0.1 



-1 



2 3 4 

Reliability Index, |3 



Figure F-M6-dResistance factor calibration for 99 cases of concrete piles in Mixed soils using the X 
and Nordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thombum) in North of Vietnam 



351 



I 




Bias Factor 

Figure F-M6-eHistogram and frequency distribution of bias factor A.6 for 41 cases of concrete piles in 
Mixed soils using the X andNordlund/Thurman method (Su: Hara, (j): Peck, Hanson and Thombum) in 
Central of Vietnam 




Reliability Index, p 



Figure F-M6-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the X 
andNordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thombum) in Central of Vietnam 



352 



LamdaeSouthMixed data 

Normal 

Log-Normal 




0.8 1 1.2 1.4 1.6 

Bias Factor 

Figure F-M6-gHistogram and frequency distribution of bias factor 1.6 for 25 cases of concrete piles in 
Mixed soils using the A, and Nordlund/Thurman method (Su: Hara, cj): Peck, Hanson and Thombum) in 
South of Vietnam 



e 

o 
o 

CC 
LL 

CD 
O 

c 
re 

CO 

CD 

CC 



1 

0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 









3 4 5 

Reliability Index, p 



Figure F-M6-h Resistance factor calibration for 25 cases of concrete piles in Mixed soils using the X and 
Nordlund/Thurman method (Su: Hara, (|): Peck, Hanson and Thombum) in South of Vietnam 



353 



Lamda7AIIMixed data 

Normal 

Log-Normal 



CO 

CD 
Q 




1 1.5 

Bias Factor 

Figure F-M7-aHistogram and frequency distribution of bias factor Xl for 165 cases of concrete piles in 
Mixed soils using the pBurland andNordlund/Thurman method ((|): Peck, Hanson and Thomburn) in 
Vietnam 




3 4 
Reliability Index, p 

Figure F-M7-bResistance factor calibration for 1 65 cases of concrete piles in Mixed soils using the 
PBurland andNordlund/Thurman method ((|): Peck, Hanson and Thornbum) in Vietnam 



354 




0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 

Bias Factor 

Figure F-M7-cHistogram and frequency distribution of bias factor Xl for 99 cases of concrete piles in 
Mixed soils using the PBurland and Nordlund/Thurman method ((|): Peck, Hanson and Thombum) in 
North of Vietnam 




Reliability Index, p 



Figure F-M7-dResistance factor calibration for 99 cases of concrete piles in Mixed soils using the 
PBurland and Nordlund/Thurman method (c|): Peck, Hanson and Thombum) in North of Vietnam 



355 



LamdayCentrallVlixed data 

Normal 

Log-Normal 




0.6 0.8 1 1.2 1.4 1.6 1.8 

Data 

Figure F-M7-eHistogram and frequency distribution of bias factor Xl for 4 leases of concrete piles in 
Mixed soils using the P Burland and Nordlund/Thurman method ((|): Peck, Hanson and Thombum) in 
Central of Vietnam 




1 2 3 4 5 6 7 

Reliability Index, p 



Figure F-M7-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the 
PBurland andNordlund/Thurman method ((|): Peck, Hanson and Thombum) in Central of Vietnam 



356 




Figure F-M7-gHistogram and frequency distribution of bias factor A.7 for 25 cases of concrete piles in 
Mixed soils using the PBurland andNordlund/Thurman method ((}): Peck, Hanson and Thomburn) in 
South of Vietnam 



1 




Q "I I \ \ \ \ \ \ \ \ \ [ 

■ 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 

Reliability Index, (3 

Figure F-M7-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using the 
PBurland andNordlund/Thurman method (cj): Peck, Hanson and Thomburn) in South of Vietnam 



357 



T 




Bias Factor 

Figure F-M8-aHistogram and frequency distribution of bias factor A.8 for 165 cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Peck, (|): Schmertmann) in 
Vietnam 




Reliability Index, p 

Figure F-M8-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Peck, (j): Schmertmann) in Vietnam 



358 




0.2 0.4 0.6 0.8 1 1.2 1.4 

Bias Factor 



Figure F-M8-cHistogram and frequency distribution of bias factor A.8 for 99 cases of concrete piles in 
Mixed soils using the a-Tomlinson and Nordlund/Thurman method (Su: Peck, (|): Schmertmann) in North 
of Vietnam 




Reliability Index, p 



Figure F-M8-dResistance factor calibration for 99 cases of concrete piles in Mixed soils using the a- 
Tomlinson and Nordlund/Thurman method (Su: Peck, (|): Schmertmann) in North of Vietnam 



359 



LamdaSCentralMixed data 

Normal 

Log-Normal 




1 1.2 
Bias Factor 

Figure F-M8-eHistogram and frequency distribution of bias factor A.8 for 4 leases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Peck, cj): Schmertmann) in 
Central of Vietnam 




-1 1 2 3 4 5 6 

Reliability Index, p 



Figure F-M8-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Peck, (j): Schmertmann) in Central of Vietnam 



360 



2.5 



LamdaSSouthMixed data 
Normal 
■ Log-Normal 




0.8 1 1.2 1.4 1.6 

Bias Factor 

Figure F-M8-gHistogram and frequency distribution of bias factor A.8 for 25 cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Peck, cj): Schmertmann) in South 
of Vietnam 



o 

-I—' 

o 

LL 
CD 

o 

ro 
^— ' 
w 

w 

(D 
DC 




1.5 2 2.5 
Reliability Index, p 



3.5 





4 



4.5 



Figure F-M8-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Peck, (|): Schmertmann) in South of Vietnam 



361 




Bias Factor 

Figure F-M9-aHistogram and frequency distribution of bias factor A.9 for 165 cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Hara, (|):Schmertmann) in 
Vietnam 




Reliability Index, p 



Figure F-M9-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Hara, (j):Schmertmann) in Vietnam 



362 




0.2 0.4 0.6 0.8 1 1.2 

Bias Factor 



Figure F-M9-cHistogram and frequency distribution of bias factor A.9 for 99cases of concrete piles in 
Mixed soils using the a-Tomlinson and Nordlund/Thurman method (Su: Hara, (|):Schmertmann) in North 
of Vietnam 




Reliability Index, p 

FigureF-M9-dResistance factor calibration for 99cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Hara, (|): Schmertmann) in North of Vietnam 



363 



0.8 

Bias Factor 



LamdaQCentralMixed data 

Normal 

Log-Normal 




Figure F-M9-eHistogram and frequency distribution of bias factor A.9 for 41cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Hara, (|):Schmertmann) in Central 
of Vietnam 




-1 1 2 3 4 5 

Reliability Index, p 

Figure F-M9-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Hara, (j):Schmertmann) in Central of Vietnam 



364 



Lamda9SouthMixed data 

Normal 

Log-Normal 




0.8 

Bias Factor 



1.4 



Figure F-M9-gHistogram and frequency distribution of bias factor A.9 for 25 cases of concrete piles in 
Mixed soils using the a-Tomlinson andNordlund/Thurman method (Su: Hara, cj): Schmertmann) in South 
of Vietnam 



CD 

o 
c 

CO 

CD 
DC 



1 p 

0.9 
0.8 

0.7- 
0.6 
0.5 - 
0.4 - 
0.3 
0.2^ 




Reliability Index, p 

Figure F-M9-hResistance factor calibration for 25cases of concrete piles in Mixed soils using the a- 
Tomlinson andNordlund/Thurman method (Su: Hara, (|): Schmertmann) in South of Vietnam 



365 



1.4 - 




0.5 1 1.5 2 

Bias Factor 

Figure F-MlO-aHistogram and frequency distribution of bias factor >.10 for 165 cases of concrete piles in 
Mixed soils using the a-API andNordlund/Thurman method (Su: Peck, (j): Schmertmann) in Vietnam 




Reliability Index, (3 

Figure F-MlO-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Peck, (|): Schmertmann) in Vietnam 



366 



1.8 




0.5 1 1.5 

Bias Factor 



Figure F-MlO-c Histogram and frequency distribution of bias factor A,10 for 99 cases of concrete piles in 
Mixed soils using the a- API and Nordlund/Thurman method (Su: Peck, (|): Schmertmann) in North of 
Vietnam 




Reliability Index, (3 



Figure F-MlO-dResistance factor calibration for 99 cases of concrete piles in Mixed soils using the a- 
API and Nordlund/Thurman method (Su: Peck, cj): Schmertmann) in North of Vietnam 



367 




Bias Factor 

Figure F-MlO-eHistogram and frequency distribution of bias factor >.10 for 4 leases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Peck, cj): Schmertmann) in Central of 
Vietnam 



1.2 




Reliability Index, p 

Figure F-MlO-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Peck, (|): Schmertmann) in Central of Vietnam 



368 



Lamdal OSouthMixed data 

Normal 

Log-Normal 




0.8 1 
Bias Factor 



Figure F-MlO-gHistogram and frequency distribution of bias factor A.10 for 25 cases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Peck, cj):Schmertmann) in South of 
Vietnam 




Reliability Index, p 

Figure F-MlO-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Peck, (|):Schmertmann) in South of Vietnam 



369 




Reliability Index, p 

Figure F-Ml 1-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Hara, (j): Schmertmann) in Vietnam 



370 




0.2 0.4 0.6 0.8 1 

Bias Factor 

Figure F-Mll-cHistogram and frequency distribution of bias factor A.1 1 for 99 cases of concrete piles in 
Mixed soils using the a-API and Nordlund/Thurman method (Su: Hara, (|): Schmertmann) in North of 
Vietnam 




Reliability Index, p 

Figure F-Mll-dResistance factor calibration for 99 cases of concrete piles in Mixed soils using the a- 
API and Nordlund/Thurman method (Su: Hara, (|): Schmertmann) in North of Vietnam 



371 



Lamdal 1 CentralMixed data 

Normal 

Log-Normal 




Bias Factor 

Figure F-Ml l-eHistogram and frequency distribution of bias factor A.1 1 for 41 cases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Hara, (|): Schmertmann) in Central of 
Vietnam 




Reliability Index, p 

Figure F-Ml 1-fResistance factor calibration for 41 cases of concrete piles in Mixed soils using 
the a-API and Nordlund/Thurman method (Su: Hara, cj): Schmertmann) in Central of Vietnam 



372 




Figure F-Ml 1-gHistogram and frequency distribution of bias factor A.1 1 for 25cases of concrete piles in 
Mixed soils using the a- API andNordlund/Thurman method (Su: Hara, (j): Schmertmann) in South of 
Vietnam 




Reliability Index, p 



Figure F-Ml 1-h Resistance factor calibration for 25 cases of concrete piles in Mixed soils using the a- 
API andNordlund/Thurman method (Su: Hara, (j): Schmertmann) in South of Vietnam 



373 



1.4 - 




Bias Factor 

Figure F-M12-aHistogram and frequency distribution of bias factor A. 12 for 165 cases of concrete piles in 
Mixed soils using the X and Nordlund/Thurman method (Su: Peck, (j): Schmertmann) in Vietnam 




Reliability Index, p 

Figure F-M12-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the X 
andNordlund/Thurman method (Su: Peck, (j): Schmertmann) in Vietnam 



374 




0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 

Bias Factor 



Figure F-M12-cHistogram and frequency distribution of bias factor A.12 for 99 cases of concrete piles in 
Mixed soils using the 'k and Nordlund/Thurman method (Su: Peck, (j): Schmertmann) in North of Vietnam 




Reliability Index, p 

Figure F-M12-dResistance factor calibration for 99 cases of concrete piles in Mixed soils using the X 
and Nordlund/Thurman method (Su: Peck, (|): Schmertmann) in North of Vietnam 



375 



Lamdal 2CentralMixed data 

Normal 

Log-Normal 




1.2 1.4 1.6 1.8 2 2.2 2.4 

Bias Factor 

Figure F-M12-eHistogram and frequency distribution of bias factor X\2 for 41 cases of concrete piles in 
Mixed soils using the 7^ andNordlund/Thurman method (Su: Peck, (|): Schmertmann) in Central of 
Vietnam 



1.2 
1.1 

1 

e 0.9 

Q 

0.8 
ns 

LL 

1 0.7 
I 0.6 

0) 

^ 0.5 
0.4 
0.3 
0.2 








0.5 



1.5 2 2.5 3 
Reliability Index, (3 




4.5 



Figure F-M12-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the X 
andNordlund/Thurman method (Su: Peck, cj): Schmertmann) in Central of Vietnam 



376 




Figure F-M12-gHistogram and frequency distribution of bias factor A.12 for 25cases of concrete piles in 
Mixed soils using the X andNordlund/Thurman method (Su: Peck, (|): Schmertmann) in South of Vietnam 

1 

0.9 
0.8 

e 

i£ 0.6 
i 0.5 

0.4 

cc 

0.3 
0.2 



0.1 



-0.5 




0.5 



1.5 2 
Reliability Index, p 



2.5 



3.5 



Figure F-M12-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using the A, 
andNordlund/Thurman method (Su: Peck, (|): Schmertmann) in South of Vietnam 



377 




Reliability Index, (3 



Figure F-M13-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the 'k 
andNordlund/Thurman method (Su: Hara, (j): Schmertmann) in Vietnam 



378 



1.5 



0.5 



Lamda13NorthMixed data 

Normal 

Log-Normal 



0.2 



0.4 



0.6 

Bias Factor 



0.8 



1.2 



Figure F-M13-cHistogram and frequency distribution of bias factor >.13 for 99 cases of concrete piles in 
Mixed soils using the A, andNordlund/Thurman method (Su: Hara, (j): Schmertmann) in North of Vietnam 




e 

o 

CO 

u. 

CD 
O 
£Z 

iS 
05 0.4 



0.3 



0.2 - 



2 3 
Reliability Index, p 



Figure F-M13-dResistance factor calibration for 99cases of concrete piles in Mixed soils using the X 
andNordlund/Thurman method (Su: Hara, (j): Schmertmann) in North of Vietnam 



379 




0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 

Bias Factor 



Figure F-M13-eHistogram and frequency distribution of bias factor A. 13 for 41 cases of concrete piles in 
Mixed soils using the X andNordlund/Thurman method (Su: Hara, (|): Schmertmann) in Central of 
Vietnam 




Q 2 I f ^ \ \ f ^ ^ """""""t- I 

1 2 3 4 5 6 7 8 

Reliability Index, p 

Figure F-M13-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the X 
andNordlund/Thurman method (Su: Hara, cj): Schmertmann) in Central of Vietnam 



380 




0.2 0.4 0.6 0.8 1 1.2 

Bias Factor 



Figure F-M13-gHistogram and frequency distribution of bias factor A. 13 for 25 cases of concrete piles in 
Mixed soils using the X andNordlund/Thurman method (Su: Hara, (|): Schmertmann) in South of Vietnam 




Reliability Index, p 



Figure F-M13-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using the A, 
andNordlund/Thurman method (Su: Hara, (j): Schmertmann) in South of Vietnam 



381 




0.5 1 1.5 2 

Bias Factor 



Figure F-M14-aHistogram and frequency distribution of bias factor A. 14 for 165 cases of concrete piles in 
Mixed soils using the pBurland andNordlund/Thurman method Schmertmann) in Vietnam 




Reliability Index, p 

Figure F-M14-bResistance factor calibration for 165 cases of concrete piles in Mixed soils using the 
PBurland andNordlund/Thurman method Schmertmann) in Vietnam 



382 



1.6 
1.4 
1.2 



CO 

I 0.8 



0.6 
0.4 
0.2 







0.2 



0.4 



Lamdal 4NorthMixed data 
■ Normal 
Log-Normal 



0.6 0.8 
Bias Factor 



1.2 



1.4 



Figure F-M14-C Histogram and frequency distribution of bias factor X\4 for 99 cases of concrete piles in 
Mixed soils using the PBurland and Nordlund/Thurman method ((j):Schmertmann) in North of Vietnam 



1 

0.9 
0.8 



e 



-■^ 0.7 



o 
o 

LL 



0.6 



o 

5 0.5 



0.4 
0.3 
0.2 
0.1 




-1 







1 



2 3 4 5 6 

Reliability Index, p 

Figure F-M14-dResistance factor calibration for 99 cases of concrete piles in Mixed soils using the 
PBurland and Nordlund/Thurman method (cj):Schmertmann) in North of Vietnam 



383 



T 




Bias Factor 

Figure F-M14-eHistogram and frequency distribution of bias factor A. 14 for 4 leases of concrete piles in 
Mixed soils using the PBurland andNordlund/Thurman method (cj):Schmertmann) in Central of Vietnam 





■ 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 

Reliability Index, p 

Figure F-M14-fResistance factor calibration for 4 leases of concrete piles in Mixed soils using the 
PBurland andNordlund/Thurman method ((|):Schmertmann) in Central of Vietnam 



384 



Lamdal 4SouthMixed data 

Normal 

Lognormal 




0.8 1 
Bias Factor 



Figure F-M14-gHistogram and frequency distribution of bias factor A.14 for 25cases of concrete piles in 
Mixed soils using the PBurland andNordlund/Thurman method (cj):Schmertmann) in South of Vietnam 




Q -| I \ I \ \ I \ \ I I- - 

-0.5 0.5 1 1.5 2 2.5 3 3.5 4 

Reliability Index, p 

Figure F-M14-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using the 
PBurland andNordlund/Thurman method ((j):Schmertmann) in South of Vietnam 



385 




■I I I I \ \ I I I I I- 

'01 23456789 

Reliability Index, (3 



Figure F-M15-bResistance factor calibration for 165cases of concrete piles in Mixed soils using the 
Schmertmann SPT method in Vietnam 



386 



Lamdal SNorthMixed data 

Normal 

Lognormal 




1.5 

Bias Factor 

Figure F-M15-cHistogram and frequency distribution of bias factor XI 5 for 99 cases of concrete piles in 
Mixed soils using the Schmertmann SPT method in North of Vietnam 




4 5 6 7 8 9 

Reliability Index, (3 

Figure F-M15-dResistance factor calibration for 99 cases of concrete piles in Mixed soils using the 
Schmertmann SPT method in North of Vietnam 



387 




0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 

Bias Factor 

Figure F-M15-eHistogram and frequency distribution of bias factor A.15 for 4 leases of concrete piles in 
Mixed soils using the Schmertmann SPT in Central of Vietnam 



1.2 




0.2 1 ^ ' ^ ^ 1 ^ ^ 1 

-1 1 2 3 4 5 6 

Reliability Index, (3 

Figure F-M15-fResistance factor calibration for 41cases of concrete piles in Mixed soils using the 
Schmertmann SPT in Central of Vietnam 



388 




Reliability Index, (3 



Figure F-M15-hResistance factor calibration for 25 cases of concrete piles in Mixed soils using 
theSchmertmann SPTmethod ((|):Schmertmann) in South of Vietnam 



389 



APPENDIX G 
Nominal and Measure Capacity of 
Drilled Shaft from Vietnam 



Table G-1 Summary drilled shaft data from Vietnam 



No 


Name of Project 


Location 


Soil 


Name 


(mm) 


(m) 


NP-Ml 


181 Nguyen Luong Bang-Hanoi 


Hanoi 


Mixed 


C9 


1 


47 


NP-M2 




North Plain 




C26 


0.8 


47 


NP-M3 


Chung Cu Cao Tang CT4-Van Khe 


Hanoi 


Mixed 


TN-1 


1.2 


44 


NP-M4 


HaDong-HaTay 


North Plain 




TN-2 


1.2 


44 


NP-M5 








TN-3 


1.2 


44 


NP-M6 


CTIA-CTIB- Xuan La-Tayho-Hanoi 


Hanoi 


Mixed 


TN08 


1.2 


44 


NP-M7 




North Plain 




TN22 


1.0 


44 


NP-M8 








TN26 


1.2 


44 


NP-M9 


CT3 Trung Van-Hanoi 


Hanoi 


Mixed 


NTl 


1.2 


46 


NP-MIO 




North Plain 




NT2 


1.2 


46 


NP-Ml 1 








NT3 


1.0 


44 


NP-Ml 2 








NT4 


1.0 


45 


NP-Ml 3 








NT5 


0.8 


46 


NP-Ml 4 


1 1 Tran Hung Dao-Hanoi 


Hanoi 


Mixed 


TNI 


1.0 


44 


NP-Ml 5 




North Plain 




TN2 


0.8 


44 


NP-M16 


235 Nguyen Trai-Hanoi 


Hanoi 


Mixed 


TNI -07 


1.0 


46 


NP-Ml 7 




North Plain 




TN2-32 


1.0 


46 


NP-Ml 8 


Habico-Tower-Hanoi 


Hanoi 


Mixed 


N07 


1.2 


40 


NP-Ml 9 




North Plain 




N207 


1.2 


40 


NP-M20 








N223 


1.5 


40 


NP-M21 








N44 


1.2 


40 


NP-M22 


Hanoi Central Hotel-44 Ly ThuongKiet St 


Hanoi 


Mixed 


No60 


1.0 


39 


NP-M23 


Hanoi Tung Shing Club- 151 ThuyKhe- 


Hanoi 


Mixed 


P65 


1.2 


52 


NP-M24 


Tay Ho-Hanoi 


North Plain 




P119 


1.2 


52 


NP-M25 








P216 


1.2 


51 


NP-M26 








P290 


1.0 


41 


NP-M27 


La Khe-Van Khe, Ha Dong-HaTay 


Hanoi 


Mixed 


CN120-14 


1.2 


49 


NP-M28 




North Plain 


Sand 


CN 100-03 


1.0 


49 


NP-M29 


Logitem Vietnam Corp, Nol project-Thai Thinh 


Hanoi 


Mixed 


C-45 


1.0 


47 


NP-M30 


M5 Tower-Nguyen Chi Thanh-Hanoi 


Hanoi 




TN2-96 


1.5 


47 


NP-M31 


NhaKhoSach-Thu VienQuocGia-Hanoi 


Hanoi 


Mixed 


No-2 


0.9 


46 


NP-M32 




North Plain 




No-3 


0.9 


45 


NP-M33 


Nha van phong 149-pho Hue-hanoi 


Hanoi 


Mixed 


TNOl-50 


0.4 


42 


NP-M34 




North Plain 




TN02-123 


0.4 


43 


NP-M35 


Thanh Tri Bridge-Hanoi 


Hanoi 


Mixed 


P18 


1.5 


42 


NP-M36 




North Plain 




P32 


1.5 


42 


NP-M37 








P11-L8 


1.5 


49 


NP-M38 








P12-R02 


1.5 


50 


NP-M39 








P12-R05 


1.5 


50 


NP-M40 


Trung Tam Thuong Mai CauGiay-DichVong 


Hanoi 




No27 


1.2 


47 


NP-M41 


CauGiay-Hanoi 


North Plain 




No92 


1.2 


44 


NP-M42 


Trung Tam Thuong Mai-Khu do thi 


Hanoi 


Mixed 


TN07 


1.0 


37 


NP-M43 


Nam Thang Long-Tay Ho-Hanoi 


North Plain 


more 


TN16 


1.0 


37 


NP-M44 






Sand 


TN08 


1.0 


37 


NP-M45 








TN04 


0.8 


37 


NP-M46 








TNll 


1.0 


37 



390 



Tabl 


eG-1 (cont.) 


NP-M47 








TN15 


1.0 


37 


NP-M48 








TN03 


1.2 


37 


NP-M49 








TN12 


1.0 


37 


NP-M50 


Ever Fortune Plaza Hote 1- 83 Ly ThuongKiet 


Hanoi 




D5a 


1.0 


40 


NP-M51 


Hanoi Opera Hilton - Hanoi 


Hanoi 


Mixed 


2.00 


1.0 


38 


NP-M52 


Phap Van Bridge - Hanoi 


Hanoi 




P38R32 


1.2 


44 


NP-M53 


SaS Royal Hotel-LeNin Park-Hanoi 


Hanoi 




TPl 


1.0 


43 


NP-M54 




North Plain 




TP2 


0.8 


43 


NP-M55 


Tru So Bo Noi Vu-Khu Do thimoiDichVong 


Hanoi 


Mixed 


TN2 


1.0 


52 


NP-M56 


CauGiay-Hanoi 


North Plain 




TN3 


1.0 


51 


NP-M57 








TN4 


1.0 


51 


NP-M58 


Trung Tam Thuong Mai Dich Vu 


Hanoi 




TNI 


1.2 


50 


NP-M59 


1 14 Mai Hac De Hanoi 


North Plain 




TN2 


1.0 


50 


NP-M60 


Indochina Plaza-Hanoi-straingage 


Hanoi 




TPl 


1.0 


58 


NP-M61 




North Plain 




TP2 


1.5 


48 


NP-M62 








TP3 


0.6-2.7 


40 


NP-M63 


My Dinh- TuLiem - Hanoi 


Hanoi 




N62 


1.2 


41 


NP-M64 




North Plain 




NlOO 


1.5 


42 


NP-M65 








N207 


1.5 


42 


NP-M66 


349 Doi Can-Hanoi 


Hanoi 




CN2-10 


1.2 


36 


NP-M67 




North Plain 




CNl-44 


1.2 


36 


NP-M68 


1 14 Mai Hac De -Hanoi 


Hanoi 




TNI 


1.2 


49 


NP-M69 




North Plain 




TN2 


1.5 


49 


NP-M70 


Ngoc Khanh -Ba Dinh-Hanoi 


Hanoi 




42.00 


1.2 


43 


NP-M71 




North Plain 




195.00 


0.8 


43 


NP-M72 


B15 - Dai Kim-Dinh Cong-Hanoi 


Hanoi 




Nol3 


1.0 


48 


NP-M73 




North Plain 




No68 


1.0 


60 


NP-M74 








N0II8 


1.0 


48 


NP-M75 


335 Duong CauGiay-Hanoi 


Hanoi 


Mixed 


TNOl-05 


1.0 


44 


NP-M76 




North Plain 


more 


TN03-54 


1.2 


44 


NP-M77 






sand 


TN02-36 


1.2 


44 


NP-M78 








TN04-94 


1.2 


44 


NP-M79 


Thuong Ly Bridge - HaiPhong 


Hanoi 


Mixed 


K35-M3 


1.0 


59 


NP-M80 


LachChay Bridge -HaiPhong 


HaiPhong 


Mixed 


No2D 


1.0 


53 


NP-M81 


An Duong Bridge - HaiPhong 


HaiPhong 


Mixed 


N16 


1.5 


51 


NP-M82 




North Mountain 




N06 


1.0 


48 


NP-M83 








N07 


1.0 


46 


NP-M84 








NIO 


1.0 


42 


NP-M85 


Truong DH Hung Vuong-Viet Tri-VinhPhu 


Viet Tri 




TNOl 


1.2 


39 


NP-M86 




North Mountain 




TN06 


1.2 


34 


CP-MI 


Cau qua Song han-Danang 


Danang 




A-8 


1.5 


37 


CP-M2 




Central Plain 




P-5 


2.0 


36 


SP-Ml 


Cao Octrung cu PhuThanh-SaiGon 


SaiGon 




No-73 


1.0 


32 


SP-M2 




South Plain 




No-356 


1.0 


32 


SP-M3 


193 dinhthienhoang-PDakao-saigon 


SaiGon 




TNOl 


0.8 


43 


SP-M4 




South Plain 




TN02 


1.0 


43 


SP-M5 


Duong Cao Toe TrungLuong-SaiGon 


SaiGon 




C5-T27 


1.0 


54 


SP-M6 




South Plain 




C4-T29 


1.0 


53 



Tabl 


eG-1 (cont.) 


SP-M7 








C4-T31 


1.0 


55 


SP-M8 








C7-T37 


1.0 


52 


SP-M9 








C7-T39 


1.0 


52 


SP-MIO 








C12-T45 


1.0 


54 


SP-Mll 








N14-T4 


1.5 


46 


SP-M12 


Highrise building Sonadezi-Bien Hoa 


SaiGon 




CN80-14 


0.8 


21 


SP-M13 


Saigon 


South Plain 




CN80-32 
CNIOO- 


0.8 


17 


SP-M14 








132 


1.0 


20 


SP-M15 








CN 100-35 


1.0 


20 


SP-M16 


Hung Long comany-SaiGon 


SaiGon 




CTT06 


1.2 


60 


SP-M17 




South Plain 




CTT07 


1.2 


60 


SP-M18 


Trung Cu UngThanhHao Mon -Phuong 7-Q8 


SaiGon 




N01-CN2 


1.0 


60 


SP-M19 


SaiGon 


South Plain 




N02-CN1 


1.0 


60 



Table G-2 Summary measure capacity of drilled shaft from North, Central and South of Vietnam 
by different criterion 





Design 
















Load 


SLT 




Measure Capacity 






iNO 


(1) 


(1) 


Chin's Method 


80% rhin's Mpthorl 




1 


U.JTcU 


NP-Ml 


260 


520 


877 


709 


/ OJ 


735 


783 


NP-M/ 


260 


520 


909 


727 


0\J\J 


756 


or\r\ 

800 


NP-M3 


700 


1400 


2000 


1 ^>oo 

LOW 


1 son 


1300 


1652 


NF-M4 


700 


1 4 r\f\ 

1400 


2000 


1 600 


±'-ry\J 


1320 


1648 


NP-M5 


700 


1400 


2000 


1600 


1680 


1520 


1730 


NP-M6 


600 


1200 


3333 


2667 


2100 


1550 


2250 


NP-M7 


450 


900 


2000 


1600 


1700 


1540 


1780 


NP-M8 


600 


1200 












NP-M9 


550 


1100 


2222 


1778 


1460 


1310 


1728 


NP-MIO 


550 


1100 


2128 


1702 


1620 


1480 


1807 


NP-Ml 1 


370 


740 


1754 


1404 


1324 


1154 


1442 


NP-M12 


370 


740 


1370 


1096 


1121 


1045 


1186 


NP-Ml 3 


250 


500 


1316 


1053 


1000 


950 


1098 


NP-M14 


400 


800 


1205 


964 


1010 


950 


1065 


NP-M15 


300 


600 


1042 


833 


810 


720 


816 


NP-M16 


470 


940 


1429 


1143 


1250 


1160 


1279 


NP-M17 


470 


940 


1429 


1143 


1290 


1200 


1305 


NP-Ml 8 


883 


1766 


2941 


2353 


2200 


1900 


2390 


NP-M19 


804 


1609 


2778 


2222 


1964 


1721 


2212 


NP-M20 


1055 


2109 


2857 


2286 


2200 


1900 


2370 


NP-M21 


883 


1766 


2500 


2000 


1800 


1600 


2036 


NP-M22 


300 


750 


1429 


1143 


850 


800 


1014 


NP-M23 


650 


1300 


2564 


2051 


2050 


1682 


2104 


NP-M24 


650 


937 












NP-M25 


650 


1031 












NP-M26 


400 


707 












NP-M27 


550 


1100 


2000 


1600 


1600 


1300 


1633 


NP-M28 


450 


900 


1887 


1509 


1500 


1250 


1508 


NP-M29 


220 


330 


526 


421 


450 


460 


494 



392 



Table G-2 (cont.) 



NP-M30 


1000 


2000 


3846 


3077 


2419 


2050 


2980 


NP-M31 


300 


450 


812 


649 


685 


650 


713 


NP-M32 


300 


450 


888 


710 


672 


629 


722 


NP-M33 


70 


105 












NP-M34 


70 


105 












NP-M35 


501 


1002 


1754 


1404 


1510 


1462 


1645 


NP-M36 


671 


1341 


2000 


1379 


1340 


1270 


1540 


NP-M37 


432 


864 


2439 


1951 


1937 


1748 


2186 


NP-M38 


501 


1002 


1667 


1333 


1440 


1400 


1560 


NP-M39 


501 


1002 


2703 


2162 


2000 


1800 


2312 


NP-M40 


570 


1140 


1887 


1509 


1577 


1470 


1653 


NP-M41 


570 


1140 


1887 


1509 


1470 


1380 


1594 


NP-M42 


450 


900 


1429 


1143 


1185 


1082 


1232 


NP-M43 


450 


900 


1429 


1143 


1167 


1072 


1225 


NP-M44 


450 


900 


1429 


1143 


1150 


1050 


1210 


NP-M45 


300 


600 


1429 


1143 


1200 


1100 


1250 


NP-M46 


450 


900 


1429 


1143 


1163 


1068 


1222 


NP-M47 


450 


900 


1429 


1143 


1237 


1162 


1282 


NP-M48 


600 


1200 


1111 


889 


951 


910 


1000 


NP-M49 


450 


900 


1429 


1143 


1100 


1000 


1185 


NP-M50 


435 


870 


1808 


1447 


1195 


1025 


1308 


NP-M51 




960 


1890 


1512 


1300 


1095 


1387 


NP-M52 




790 


1460 


1168 


1113 


1043 


1250 


NP-M53 




770 


1235 


988 


975 


900 


1042 


NP-M54 




370 


575 


460 


460 


450 


493 


NP-M55 


550 


1100 


1701 


1361 


1512 


1348 


1504 


NP-M56 


550 


1100 


1745 


1396 


1512 


1330 


1509 


NP-M57 


550 


1100 


1582 


1266 


1375 


1195 


1361 


NP-M58 


750 


1300 


2083 


1667 


1626 


1474 


1777 


NP-M59 


400 


800 


1370 


1096 


1100 


1069 


1201 


NP-M60 


- 


2400 


5556 


4444 


4000 


2100 


3000 


NP-M61 


- 


2400 


5263 


4211 


4025 


3209 


4000 


NP-M62 


- 


2600 


3704 


2963 


2844 


2436 


3000 


NP-M63 






3333 


2667 


2206 


1850 


2350 


NP-M64 






4167 


3333 


2933 


2500 


3402 


NP-M65 






4000 


3200 


2750 


2340 


3234 


NP-M66 


750 


1500 


2439 


1951 


1826 


1600 


2000 


NP-M67 


750 


1500 


2326 


1860 


1900 


1734 


2036 


NP-M68 


1100 


2200 


3333 


2667 


2400 


1850 


2455 


NP-M69 


1550 


3100 


5263 


4211 


2712 


1935 


3400 


NP-M70 


620 


1240 


2703 


2162 


1569 


1700 


2178 


NP-M71 


270 


540 


1163 


930 


848 


800 


900 


NP-M72 


440 


880 


1961 


1569 


1367 


1125 


1400 


NP-M73 


440 


880 


2222 


1778 


1743 


1590 


1600 


NP-M74 


440 


880 


1887 


1509 


1400 


1100 


1400 


NP-M75 


450 


1000 


1408 


1127 


1200 


1125 


1257 


NP-M76 


600 


1200 


1724 


1379 


1472 


1400 


1553 


NP-M77 


600 


1200 


1754 


1404 


1485 


1415 


1567 



393 



Table G-2 (cont.) 



NP-M78 


600 


1200 


1754 


1404 


1500 


1425 


1601 


NP-M79 




460 


1114 


891 


890 


789 


924 


NP-M80 




450 


870 


696 


710 


750 


786 


NP-M81 




1314 


2083 


1667 


1750 


1550 


1869 


NP-M82 




527 


1235 


988 


844 


775 


927 


NP-M83 




527 


1149 


920 


900 


821 


958 


NP-M84 




527 


1064 


851 


894 


840 


939 


NP-M85 


600 


1200 


2000 


1600 


1668 


1534 


1775 


NP-M86 


600 


1200 


1429 


1143 


1266 


1238 


1342 


CP-MI 


1500 


3000 


4000 


3200 


2500 


2000 


3070 


CP-M2 


1800 


3600 


5000 


4000 


3200 


2750 


4163 


SP-Ml 


400 


657 












SP-M2 


400 


600 












SP-M3 


320 


640 


1111 


889 


879 


769 


909 


SP-M4 


450 


900 


1250 


1000 


1075 


1072 


1114 


SP-M5 




664 












SP-M6 




671 












SP-M7 




598 












SP-M8 




625 












SP-M9 




670 












SP-MIO 




682 












SP-Ml 1 


500 


750 


1000 


800 


900 


900 


965 


SP-Ml 2 


270 


540 


1000 


800 


590 


654 


752 


SP-Ml 3 


270 


540 


588 


471 


300 


405 


500 


SP-M14 


450 


900 


667 


533 


350 


654 


540 


SP-Ml 5 


450 


900 


833 


667 


480 


530 


659 


SP-M16 


620 


1240 


1429 


1143 


1178 


1150 


1307 


SP-M17 


620 


1426 


2500 


2000 


1360 


1200 


1426 


SP-Ml 8 


520 


1040 












SP-Ml 9 


520 


1040 













Table G-3 Summary Nominal Capacity of Drilled Shaft from North, Central and South of 

Vietnam by Different Method 



No 


FHWA method 


Reese and Wri 


ght method 


Su:Terzaghi, Peck 


Su: (Kara) 


Su: Terzaghi, Peck 


Su: Hara 


NP-Ml 
NP-M2 


543.80 


621.16 


585.41 


662.77 


NP-M3 
NP-M4 
NP-M5 


1238.87 


1385.92 


1309.79 


1456.84 


NP-M6 
NP-M7 
NP-M8 


1134.73 


1213.33 


1686.40 


1764.99 


NP-M9 


1134.78 


1367.76 


1230.41 


1463.39 



394 



Table G-3 (cont.) 



NP-MIO 










NP-Mll 
NP-M12 
NP-M13 


843.77 
637.30 


922.89 
700.59 


905.24 
677.37 


740.67 
740.67 


NP-M14 
NP-M15 


932.11 
714.02 


1180.96 
913.10 


893.64 
682.34 


1142.49 
881.42 


NP-M16 
NP-M17 


772.73 


1203.86 


802.19 


1233.32 


NP-M18 
NP-M19 
NP-M20 
NP-M21 


1233.76 


1729.47 


1653.25 


2148.96 


NP-M22 


696.56 


939.73 


1034.85 


1278.02 


NP-M23 
NP-M24 
NP-M25 
NP-M26 


1326.33 


1484.64 


1963.45 


2121.76 


NP-M27 
NP-M28 


1170.21 
934.61 


1452.24 
1131.77 


1646.93 
1309.66 


1928.96 
1506.82 


NP-M29 


451.34 


638.94 


403.02 


590.62 


NP-M30 


1182.18 


1885.85 


1583.55 


1885.85 


NP-M31 
NP-M32 


762.25 


852.31 


938.33 


1028.39 


NP-M33 
NP-M34 


286.36 


424.45 


389.60 


527.68 


NP-M35 
NP-M36 
NP-M37 
NP-M38 
NP-M39 


1411.24 
1365.70 
1707.37 
1633.16 
1846.02 


1581.35 
1534.11 
1976.96 
1633.16 
1846.02 


1648.57 
1716.45 
1939.74 
2030.55 
2254.86 


1818.68 
1884.86 
2209.33 
2030.55 
2254.86 


NP-M40 
NP-M41 


890.48 


1211.41 


1600.64 


1921.57 


NP-M42 
NP-M43 
NP-M44 
NP-M45 
NP-M46 
NP-M47 
NP-M48 
NP-M49 


851.67 


879.16 


1229.80 


1257.28 


NP-M50 


848.80 


1019.96 


1166.91 


1338.08 


NP-M51 


820.41 


960.99 


892.52 


1033.10 


NP-M52 


925.13 


1070.41 


824.72 


970.00 


NP-M53 
NP-M54 


729.72 
479.69 


993.55 
519.07 


814.54 
544.19 


1078.37 
583.57 



395 



Table G-3 (cont.) 



NP-M55 


1224.00 


1369.03 


1688.12 


1833.15 


NP-M56 










NP-M57 










NP-M58 


1363.62 


1607.99 


1688.94 


1933.31 


NP-M59 


1363.62 


1607.99 


1688.94 


1933.31 


NP-M60 


1268.64 


1515.86 


1891.32 


2138.53 


NP-M61 


1444.37 


1838.09 


2292.32 


2686.05 


NP-M62 


1727.57 


2372.46 


2805.57 


3450.46 


NP-M63 


1067.81 


1379.71 


1705.95 


2017.84 


NP-M64 


1508.51 


1898.37 


2377.11 


2766.98 


NP-M65 


1508.51 


1898.37 


2377.11 


2766.98 


NP-M66 


901.00 


1087.13 


1396.01 


1582.14 


NP-M67 


913.79 


1115.55 


1406.53 


1608.29 


NP-M68 


1152.42 


1659.95 


1326.40 


1833.93 


NP-M69 


1570.47 


2204.88 


1819.81 


2454.22 


NP-M70 


909.83 


1045.71 


1556.54 


1692.42 


NP-M71 


536.78 


625.61 


960.14 


1048.97 


NP-M72 


670.08 


1041.75 


830.22 


1201.89 


NP-M73 


756.41 


1082.73 


858.07 


1184.39 


NP-M74 


661.24 


1058.87 


799.55 


1197.18 


NP-M75 


776.73 


1036.98 


995.23 


1255.49 


NP-M76 


991.05 


1303.36 


1303.86 


1616.17 


NP-M77 










NP-M78 










NP-M79 


822.60 


1542.78 


978.04 


1698.22 


NP-M80 


749.81 


1210.36 


994.93 


1455.47 


NP-M81 


1132.07 


1536.67 


1749.77 


2154.37 


NP-M82 


611.91 


881.65 


730.46 


1000.20 


NP-M83 










NP-M84 










NP-M85 


1473.42 


2451.94 


1652.22 


2630.74 


NP-M86 


1253.21 


2134.29 


1338.21 


2219.29 


CP-MI 


1225.45 


1923.29 


1582.55 


2280.39 


CP-M2 


1419.35 


2254.86 


2220.06 


3055.57 


SP-Ml 










SP-M2 










SP-M3 


740.61 


813.98 


655.61 


728.97 


SP-M4 


970.74 


1089.37 


864.49 


983.12 


SP-M5 










SP-M6 










SP-M7 










SP-M8 










SP-M9 










SP-MIO 










SP-Mll 


995 


1778 


995 


1778 



396 



Table G-3 (cont.) 



SP-M12 












397.84 


616.12 


701.19 


919.46 


SP-M13 










SP-M14 


612.73 


922.14 


970.95 


1280.35 


SP-M15 










SP-M16 


1291.36 


1620.90 


1571.04 


1900.58 


SP-M17 











397 



APPENDIX H 
Histogram and Frequency Distribution of 
Bias Factor for Drilled Shaft 



0.6 



Lamdal AIIMixed data 

Normal 

Lognormal 




0.8 



1.4 1.6 1.8 
Bias Factor 



2.6 



Figure H-Ml-a. Histogram and frequency distribution of bias factor X\ for 92 cases of drilled 
shaft in Mixed soils using the FHWA method (Su: Terzaghi, Peck) and using 1" criterion in 
Vietnam 




Reliability Index, p 

Figure H-Ml-b. Resistance factor calibration for 92 cases of drilled shaft in Mixed soils using the 
FHWA method (Su: Terzaghi, Peck) and using 1" criterion in Vietnam 



398 



1.8 F 




0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 

Bias Factor 



Figure H-Ml-c. Histogram and frequency distribution of bias factor A,l for 80 cases of drilled 
shaft in Mixed soils using the FHWA method (Su: Terzaghi, Peck) and using 1" criterion in 
North of Vietnam 



1.2 




0.4 



0.3 

123456789 

Reliability Index, p 

Figure H-Ml-d. Resistance factor calibration for 80 cases of drilled shaft in Mixed soils using 
the FHWA method (Su: Terzaghi, Peck) and using 1" criterion in North of Vietnam 



399 



Lamdal SouthMixed data 

Normal 

Lognormal 



1 1.2 

Bias Factor 




1.8 



Figure H-Ml-e. Histogram and frequency distribution of bias factor X\ for 10 cases of drilled 
shaft in Mixed soils using the FHWA method (Su: Terzaghi, Peck) and using 1" criterion in 
South of Vietnam 



1.2 
1.1 



1 - 



e 0.9 

O 

0.8 

a 

Ll. 

1 0.6 

CO 

a> 

DC 0.5 



0.4 
0.3 
0.2 



"0 





3 4 5 

Reliability Index, p 



Figure H-Ml-f Resistance factor calibration for 10 cases of drilled shaft in Mixed soils using the 
FHWA method (Su: Terzaghi, Peck) and using 1" criterion in South of Vietnam 



400 




Bias Factor 

Figure H-M2-a. Histogram and frequency distribution of bias factor 12 for 92 cases of drilled 
shaft in Mixed soils using the FHWA method (Su: Hara) and using 1" criterion in Vietnam 




Reliability Index, p 

Figure H-M2-b. Resistance factor calibration for 92 cases of drilled shaft in Mixed soils using 
the FHWA method (Su: Hara) and using 1" criterion in Vietnam 



401 



T 




Bias Factor 

Figure H-M2-C. Histogram and frequency distribution of bias factor Xl for 80 cases of drilled 
shaft in Mixed soils using the FHWA method (Su: Hara) and using 1" criterion in North of 
Vietnam 




Reliability Index, p 

Figure H-M2-d. Resistance factor calibrationfor 80 cases of drilled shaft in Mixed soils using the 
FHWA method (Su: Hara) and using 1" criterion in North of Vietnam 



402 



Lamda2SouthMixed data 

Normal 

Lognormal 




0.8 0.9 

Bias Factor 

Figure H-M2-e. Histogram and frequency distribution of bias factor X2 for 10 cases of drilled 
shaft in Mixed soils using the FHWA method (Su:Hara) and using 1 " criterion in South of 
Vietnam 




2 3 
Reliability Index, (3 

Figure H-M2-f. Resistance factor calibrationfor 10 cases of drilled shaft in Mixed soils using the 
FHWA method (Su:Hara) and using 1" criterion in South of Vietnam 



403 




0.6 0.8 1 1.2 1.4 1.6 1.8 

Bias Factor 



Figure H-M3-a. Histogram and frequency distribution of bias factor X3 for 92 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Tezaghi, Peck) and using 1" 
criterion in Vietnam 




Reliability Index, p 

Figure H-M3-b. Resistance factor calibration for 92 cases of drilled shaft in Mixed soils using 
the Reese and Wright method (Su: Tezaghi, Peck) and using 1" criterion in Vietnam 



404 



LamdaSNorthMixed data 




Bias Factor 

Figure H-M3-C. Histogram and frequency distribution of bias factor X3 for 80 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Tezaghi, Peck) and using 1" 
criterion in North of Vietnam 




Reliability Index, p 

Figure H-M3-d. Resistance factor calibration for 80 cases of drilled shaft in Mixed soils using 
the Reese and Wright method (Su: Tezaghi, Peck) and using 1" criterion in North of Vietnam 



405 



LamdaSSouthMixed data 




0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 

Bias Factor 

Figure H-M3-e. Histogram and frequency distribution of bias factor X3 for 10 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su:Tezaghi, Peck) and using 1" 
criterion in South of Vietnam 



1.2 




0.2 1 ' 1 ' — ^ ^ < 1 

-1 1 2 3 4 5 6 

Reliability Index, p 

Figure H-M3-f. Resistance factor calibrationfor 10 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su:Tezaghi, Peck) and using 1" criterion in South of Vietnam 



406 



Lamda4AIIMixed data 

Normal 

Log normal 




0.4 0.6 0.8 1 1.2 1.4 1.6 

Bias Factor 

Figure H-M4-a. Histogram and frequency distribution of bias factor X4 for 92 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Hara) and using 1" criterion in 
Vietnam 



1.1 

1 



e 



o 
c 
re 



0.5_ 



-.1 1 


II 


is 






- 
- 

1 




1 ~~~i 



2 3 4 

Reliability Index, p 



Figure H-M4-b. Resistance factor calibration for 92 cases of drilled shaft in Mixed soils using 
the Reese and Wright method (Su: Hara) and using 1" criterion in Vietnam 



407 



Lamda4NorthMixed data 

Normal 

Lognormal 




0.8 1 1.2 

Bias Factor 

Figure H-M4-C. Histogram and frequency distribution of bias factor X4 for 80 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Hara) and using 1" criterion in 
North of Vietnam 



1.2 
1.1 
1 

e 0.9 

o 

y 0.8 



8 0.7 



i 0.6 
w 

^ 0.5 
0.4 
0.3 
0.2 





-1 







1 



2 3 4 5 6 7 

Reliability Index, p 

Figure H-M4-d. Resistance factor calibrationfor 80 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su: Hara) and using 1" criterion in North of Vietnam 



408 



Lamda4SouthMixed data 




0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 

Bias Factor 

Figure H-M4-e. Histogram and frequency distribution of bias factor X4 for 10 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Hara) and using 1" criterion in 
South of Vietnam 



1 

0.9 

0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 



-1 








1 2 3 4 5 6 

Reliability Index, p 

Figure H-M4-f. Resistance factor calibrationfor 10 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su: Hara) and using 1" criterion in South of Vietnam 



409 



LamdaSAIIMixed data 

Normal 
Log normal 




1 1.5 2 2.5 3 

Bias Factor 



Figure H-M5-a. Histogram and frequency distribution of bias factor XS for 92 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Tezaghi, Peclc) and using 0.5% D 
criterion in Vietnam 




3 3.5 4 4.5 5 5.5 
Reliability Index, p 

Figure H-M5-b. Resistance factor calibrationfor 92 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su: Tezaghi, Peck) and using 0.5% D criterion in Vietnam 



410 



1.5 



- LamdaSNorthMixed data 
Normal 
■ Lognormal 




1 1.5 2 2.5 3 

Bias Factor 

Figure H-M5-C. Histogram and frequency distribution of bias factor X5 for 80 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Tezaghi, Peck) and using 0.5% D 
criterion in North of Vietnam 



1.2 



e 



0.8 



0.6 



0.4 



0.2 




4 5 
Reliability Index, (3 



Figure H-M5-d. Resistance factor calibrationfor 80 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su: Tezaghi, Peck) and using 0.5% D criterion in North of Vietnam 



411 



LamdaSSouthMixed data 

Normal 

Log normal 




0.8 1 1.2 1.4 1.6 1.8 2 

Bias factor 

Figure H-M5-e. Histogram and frequency distribution of bias factor X5 for 10 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su:Tezaghi, Peck) and using 0.5% D 
criterion in South of Vietnam 




Figure H-M5-f. Resistance factor calibrationfor 10 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su:Tezaghi, Peck) and using 0.5% D criterion in South of Vietnam 



412 



1.5 



Lamda6AIIMixed data 

Normal 

Lognormal 




0.5 1 1.5 2 2.5 

Bias Factor 



Figure H-M6-a. Histogram and frequency distribution of bias factor 1.6 for 92 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Hara) and using 0.5% D criterion in 
Vietnam 




Reliability Index, (3 



Figure H-M6-b. Resistance factor calibration for 92 cases of drilled shaft in Mixed soils using 
the Reese and Wright method (Su: Hara) and using 0.5% D criterion in Vietnam 



413 



Lamda6NorthMixed data 

Normal 

Lognormal 




0.5 1 1.5 2 2.5 

Bias Factor 



Figure H-M6-C. Histogram and frequency distribution of bias factor 7^6 for 80 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Hara) and using 0.5% D criterion in 
North of Vietnam 




1 2 3 4 5 6 7 8 



Reliability Index, p 

Figure H-M6-d. Resistance factor calibration for 80 cases of drilled shaft in Mixed soils using 
the Reese and Wright method (Su: Hara) and using 0.5% D criterion in North of Vietnam 



414 



LamdaeSouthMixed data 

Normal 

Lognormal 




0.8 0.9 1 1.1 1.2 1.3 1.4 

Bias Factor 

Figure H-M6-e. Histogram and frequency distribution of bias factor A,6 for 10 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Hara) and using 0.5% D criterion in 
South of Vietnam 



1.2 
1.1 
1 



e 0.9 

o 

^ 0.8 

CO 
LL 

8 0-7 

CD 

4— ' 

CO 

en 
(D 

DC 0.5 



to 0.6 



0.4 
0.3 
0.2 




-1 



2 3 
Reliability Index, p 



Figure H-M6-f Resistance factor calibration for 10 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su: Hara) and using 0.5% D criterion in South of Vietnam 



415 



1.6 



Lamda7AIIMixed data 




Bias Factor 

Figure H-M7-a. Histogram and frequency distribution of bias factor U for 92 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Tezaghi, Peck) and using 0.5% D 
criterion in Vietnam 



1.2 




Reliability Index, (3 

Figure H-M7-b. Resistance factor calibration for 92 cases of drilled shaft in Mixed soils using 
the Reese and Wright method (Su: Tezaghi, Peck) and using 0.5% D criterion in Vietnam 



416 




0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 

Bias Factor 



Figure H-M7-C. Histogram and frequency distribution of bias factor U for 80 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Tezaghi, Peck) and using 0.5% D 
criterion in North of Vietnam 



1.2 
1.1 
1 

e 0.9 

o 

o 0.8 



8 0.7 

I 0.6 

03 

^ 0.5 



0.4 
0.3 
0.2 





III 








\ 








1 




1 1 1 1 



1 



4 5 
Reliability Index, p 



Figure H-M7-d. Resistance factor calibrationfor 80 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su: Tezaghi, Peck) and using 0.5% D criterion in North of Vietnam 



417 



Lamda7SouthMixed data 

Normal 

Lognormal 




0.5 1 1.5 

Bias Factor 



Figure H-M7-e. Histogram and frequency distribution of bias factor U for 10 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Tezaghi, Peck) and using 0.5% D 
criterion in South of Vietnam 




Reliability Index, p 



Figure H-M7-f. Resistance factor calibrationor 10 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su: Tezaghi, Peck) and using 0.5% D criterion in South of Vietnam 



418 



1.2 

Bias factor 



LamdaSAIIMixed data 

Normal 

Lognormal 




Figure H-M8-a. Histogram and frequency distribution of bias factor XS for 92 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Hara) and using 0.5% D criterion in 
Vietnam 



1.2p 
1.1 - 

1 - 

e 0.9 - 

o 

o 0.8- 



8 0.7- 



0.6- 
< 

0.5- 

0.4- 
0.3 
0.2 




"0 



3 4 
Reliability Index, (3 



Figure H-M8-b. Resistance factor calibration for 92 cases of drilled shaft in Mixed soils using 
the Reese and Wright method (Su: Hara) and using 0.5% D criterion in Vietnam 



419 



LamdaSNorthMixed data 

Normal 

Log normal 




0.5 1 1.5 2 

Bias Factor 

Figure H-M8-C. Histogram and frequency distribution of bias factor A,8 for 80 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Hara) and using 0.5% D criterion in 
North of Vietnam 



1.2r 

1.1 
1 



e 0.9 - 

o 

o 0.8- 



8 0.7^ 

c 



0.6- 




^ 0.5 



0.4- 
0.3- 
0.2 



"0 



1 



2 3 4 5 6 7 

Reliability Index, p 

Figure H-M8-d. Resistance factor calibrationfor 80 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su: Hara) and using 0.5% D criterion in North of Vietnam 



420 



LamdaSSouthMixed data 

Normal 

lognormal 




0.3 0.4 0.5 0.6 0.7 0.8 0.9 

Bias Factor 

Figure H-M8-e. Histogram and frequency distribution of bias factor XS for 10 cases of drilled 
shaft in Mixed soils using the Reese and Wright method (Su: Hara) and using 0.5% D criterion in 
South of Vietnam 




Q 2 I ^ ^ ^ ^ ^ ' ^ ' ^ I 

-0.5 0.5 1 1.5 2 2.5 3 3.5 4 

Reliability Index, f3 

Figure H-M8-f. Resistance factor calibrationfor 10 cases of drilled shaft in Mixed soils using the 
Reese and Wright method (Su: Hara) and using 0.5% D criterion in South of Vietnam 



421 



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